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Wireless Communication: Applications, Security and Reliability

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 32552

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Guest Editor
Military Communication Institute, 05-130 Zegrze Poludniowe, Poland
Interests: protection of information; electromagnetic compatibility; electromagnetic eavesdropping; electromagnetic disturbance; measurement techniques; digital signal processing; image processing
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Telecommunications and Teleinformatics Department, Wroclaw University of Technology, 50-370 Wroclaw, Poland
Interests: electromagnetic compatibility; electromagnetic disturbances; antennas and propagations; telecommunication systems; radiolocation; MIMO; wireless communication
Special Issues, Collections and Topics in MDPI journals

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Faculty of Electronics and Information Technology, The Institute of Radioelectronics and Multimedia Technology, Warsaw University of Technology, Warsaw, Poland
Interests: antenna arrays; slot antennas; beam steering; interference cancellation; wireless communication; wireless sensors; radar; millimeter-wave technology; radio frequencies; tracking; FMCW

Special Issue Information

Dear Colleagues,

Technology application in civilian and military applications is crucial to support peace enforcement around the world. The pace of technological advancement in commercial products is very fast; however, military procurement processes are characterized by an R&D phase prolonged by careful verification procedures and a long equipment operation cycle.

Sustaining life of soldiers on the battlefield depends heavily on communication means—the three main pillars of security: confidentiality, integrity, and availability, as well as an additional aspect, early detection of threats. The two fields of technology, i.e., military communications and security issues, get their inspiration from general scientific achievements; however, the application area poses additional challenges and requirements on the mechanisms and solutions. Military applications require an innovative approach, long life support, and special consideration of means that support survival in the battlefield.

Wireless communications are widely used today, but new areas of implementation are still being discovered. New applications are possible as a result of progress in many fields of science and technology. Exchanging large amounts of vital data among multiple nodes simultaneously, in a dynamically changing environment, for example, between groups of moving vehicles, imposes strict requirements on latency, reliability of information delivery, and capacity of the communication system.

Information security is a very important area of radio communication. TRANSEC and COMSEC mechanisms require pseudo-random sequence generators to perform encryption and hopping functions. This Special Issue presents one of the possible solutions based on Galois NLFSRs and multiple de Bruijn sequences.

All devices, to ensure a secure processing of information should be safe in terms of immunity from electromagnetic disturbances. Such devices have to meet a lot of EMC requirements, but immunity from electromagnetic fields is the most important, as it is connected with possibilities of use of electromagnetic weapons, and insufficient immunity of a device to such exposure can be the cause of many serious accidents threatening information security.

Today’s solutions in the area of broadly understood military security go into post-quantum cryptographic algorithms, efficient authentication schemes, vulnerabilities recognition, threat and attack detection, as well as failover, high availability, and survivability.

This Special Issue is dedicated to the presentation of various issues that affect the extension of areas of wireless communication applications, its security, and reliability. Particularly interesting are techniques supporting autonomous systems, wideband communication in different frequency bands, efficient use of spectrum, channel sensing and acquisition, radio environment map construction techniques, protection of information in the aspect of cryptography, and the selection of test methods of new IT devices from the point of view of immunity from electromagnetic fields.

Taking this into account, we would like to invite you to propose novel research in the area of communications and security that can be efficiently applied in the military domain and which would be interesting to the wide audience of the prestigious journal of Applied Sciences.

Dr. Ireneusz Kubiak
Prof. Dr. Tadeusz Wieckowski
Prof. Dr. Yevhen Yashchyshyn
Guest Editors

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Keywords

  • Wireless communication
    • frequency allocation and assignment
    • cognitive radio
    • radio environment map
    • spectrum monitoring
    • sensing
    • channel acquisition
    • wideband waveforms
    • RF propagation
    • vehicular communications
    • platooning
    • spatial interpolation
    • inverse distance weighing
    • kriging
    • 5G
    • hybrid FSO/RF systems
    • UOWC (underwater optical wireless communication)
    • optical transmission sources and detectors
    • reliability of radio communications
    • system availability
  • Cryptography
    • cryptography
    • pseudo-random generators
    • cross-join method
  • Cybersecurity
    • attack detection
    • graph analysis
    • attack graphs
    • risk assessment survivability
    • failover
    • high availability
    • efficient communications
    • AI
    • machine learning
    • post-quantum cryptography
    • SDN
    • NFV
    • cloud infrastructure
  • Electromagnetic immunity
    • electromagnetic field
    • electromagnetic disturbance
    • techniques for measuring of electromagnetic immunity
    • immunity of IT devices on electromagnetic field
    • electromagnetic eavesdropping

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Related Special Issue

Published Papers (17 papers)

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Research

27 pages, 26738 KiB  
Article
Pseudo-Coloring as an Effective Tool to Improve the Readability of Images Obtained in an Electromagnetic Infiltration Process
by Ireneusz Kubiak and Artur Przybysz
Appl. Sci. 2023, 13(17), 9496; https://doi.org/10.3390/app13179496 - 22 Aug 2023
Cited by 2 | Viewed by 1167
Abstract
The article presents a method of improving the readability of images obtained in the process of electromagnetic infiltration for sources processing information in a visual form (texts, images). The method uses the so-called technique of pseudo-coloring. The proposed method is based on LUT [...] Read more.
The article presents a method of improving the readability of images obtained in the process of electromagnetic infiltration for sources processing information in a visual form (texts, images). The method uses the so-called technique of pseudo-coloring. The proposed method is based on LUT tables using the exponential function mapping the signal level of the compromising emanations into a point of the RGB color space. The conducted analyses showed that the proposed function determining the coefficients of the LUT table is an effective tool in the process of improving the level of visual perception, i.e., it increases the perception of shapes and the ability to extract elements from the background. In image processing, LUT can be identified as a color map, i.e., a structure that reflects the gray shade of an image pixel into its color representation in the RGB color space. The proposed method assumes the use of exponential functions for this reflection. As an assessment of the effectiveness of the proposed methods of pseudo-coloring images, both a subjective assessment based on the visual perception of a group of observers and an analytical assessment, which was carried out by analyzing the contrast of the assessed images, were adopted. This allowed for the same assessment and usefulness of the proposed function in determining the RGB value in the process of pseudo-coloring of images obtained during electromagnetic infiltration. The obtained results confirmed that the proposed method significantly improves contrast parameter of images, which is also confirmed by the visual assessment of these images. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
Show Figures

Figure 1

Figure 1
<p>Basic colors.</p>
Full article ">Figure 2
<p>The relative sensitivity of the cones of the human eye.</p>
Full article ">Figure 3
<p>The method of formation of input channels for LGN.</p>
Full article ">Figure 4
<p>Reproduction of the primary colors of white light using the three components of the RGB model.</p>
Full article ">Figure 5
<p>Example of (<b>a</b>) an image containing text data reconstructed in electromagnetic infiltration and (<b>b</b>) the same image subjected to pixel amplitude thresholding (pixel amplitude value threshold of 66).</p>
Full article ">Figure 6
<p>Examples of correlation images created in the process of searching for given patterns in the reconstructed image; correlation images (<b>a</b>,<b>c</b>), the corresponding images obtained as a result of thresholding pixel amplitude values (<b>b</b>,<b>d</b>).</p>
Full article ">Figure 7
<p>Pseudo-coloring process.</p>
Full article ">Figure 8
<p>An example of the course of the exponential function <math display="inline"><semantics> <mrow> <mi>E</mi> <mfenced separators="|"> <mrow> <mi>x</mi> </mrow> </mfenced> </mrow> </semantics></math> with the basic parameters of the function: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>B</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> or (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>A</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 9
<p>Images processed on the primary side, which are the source of compromising emanations: (<b>a</b>) Arial font characters and numbers, (<b>b</b>) Times New Roman letters and numbers, (<b>c</b>) truck image, (<b>d</b>) “Lena” image, (<b>e</b>) the word “protection” in Arial font, and (<b>f</b>) a photo of the inside of an anechoic chamber.</p>
Full article ">Figure 10
<p>Examples of analyzed images reconstructed on the basis of registered compromising emanations subjected to the pseudo-coloring process: (<b>a</b>) Acer projector, cooperating computer set 1280 × 1024/60, HDMI graphics standard, reception frequency of the compromising emanations <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>742</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, receiver bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, letters and numbers in Arial font; (<b>b</b>) computer set, 1024 × 768/60, VGA graphics standard, reception frequency of the compromising emanations <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>68</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, receiver band <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>68</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, letters and numbers in Times New Roman font; (<b>c</b>) computer set, standard, 1280 × 1024/60, graphic HDMI, reception frequency of the compromising emanations <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, receiver band <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, photo of trucks; (<b>d</b>) VoIP terminal display, reception frequency of the compromising emanations <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>800</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, receiver band <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, photo showing the “Lena” image; (<b>e</b>) computer set, 1024 × 768/60, HDMI graphics standard, reception frequency of the compromising emanations <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>642</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, receiver band <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>100</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, the word “protection” in Arial font; (<b>f</b>) computer set, standard, 1280 × 1024/60, graphic HDMI, reception frequency of the compromising emanations <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>o</mi> </mrow> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, receiver band <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">z</mi> </mrow> </semantics></math>, photo showing the inside of an anechoic chamber.</p>
Full article ">Figure 11
<p>Example of exponential function waveforms for RGB channels for different parameters of the function described by relation (1), R channel: <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>B</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>R</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>160</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>A</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>R</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>R</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>R</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>130</mn> </mrow> </semantics></math>, kanał G: <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>B</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>G</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>36</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>A</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>G</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>80</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>G</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>255</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>G</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, channel B: <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>B</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>B</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>A</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>B</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>120</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>B</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>140</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>B</mi> </mrow> </msub> </mrow> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.</p>
Full article ">Figure 12
<p>Typical color palettes used in commercial rasters: (<b>a</b>) “Hot I”, (<b>b</b>) “Radar II”.</p>
Full article ">Figure 13
<p>Narrowing the range of color variation for the analyzed color palettes: (<b>a</b>) “Hot II”, (<b>b</b>) “Hot III”, (<b>c</b>) “Radar II”, (<b>d</b>) “Radar III”.</p>
Full article ">Figure 14
<p>The process of obtaining images for which the contrast value is calculated according to Equation (6).</p>
Full article ">Figure 15
<p>The result of applying the pseudo-coloring algorithm to the images shown in: (<b>a</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>a, (<b>b</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>b, (<b>c</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>c, (<b>d</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>d, (<b>e</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>e, (<b>f</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>f, using the “Hot” color palette with the parameters of the exponential function <math display="inline"><semantics> <mrow> <mi>E</mi> <mfenced separators="|"> <mrow> <mi>x</mi> </mrow> </mfenced> </mrow> </semantics></math> specified in <a href="#applsci-13-09496-t001" class="html-table">Table 1</a>.</p>
Full article ">Figure 16
<p>The result of applying the pseudo-coloring algorithm to the images shown in: (<b>a</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>a, (<b>b</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>b, (<b>c</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>c, (<b>d</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>d, (<b>e</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>e, (<b>f</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>f, using the “Radar” color palette with the parameters of the exponential function <math display="inline"><semantics> <mrow> <mi>E</mi> <mfenced separators="|"> <mrow> <mi>x</mi> </mrow> </mfenced> </mrow> </semantics></math> specified in <a href="#applsci-13-09496-t002" class="html-table">Table 2</a>.</p>
Full article ">Figure 17
<p>Images after applying the pseudo-coloring algorithm, color palette, and waveforms of the <math display="inline"><semantics> <mrow> <mi>E</mi> <mfenced separators="|"> <mrow> <mi>x</mi> </mrow> </mfenced> </mrow> </semantics></math> function for each RGB channel corresponding to images in: (<b>a</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>a, (<b>b</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>b, (<b>c</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>c, (<b>d</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>d, (<b>e</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>e, (<b>f</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>f, for the parameters <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>A</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>B</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> presented in <a href="#applsci-13-09496-t003" class="html-table">Table 3</a>.</p>
Full article ">Figure 17 Cont.
<p>Images after applying the pseudo-coloring algorithm, color palette, and waveforms of the <math display="inline"><semantics> <mrow> <mi>E</mi> <mfenced separators="|"> <mrow> <mi>x</mi> </mrow> </mfenced> </mrow> </semantics></math> function for each RGB channel corresponding to images in: (<b>a</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>a, (<b>b</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>b, (<b>c</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>c, (<b>d</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>d, (<b>e</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>e, (<b>f</b>) <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>f, for the parameters <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>A</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>B</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math> presented in <a href="#applsci-13-09496-t003" class="html-table">Table 3</a>.</p>
Full article ">Figure 18
<p>Perceptual evaluation of images obtained in the process of pseudo-coloring the image from <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>a for the “Hot” and “Radar” palettes and proposed by the authors (“Own”): (<b>a</b>) women, (<b>b</b>) men, (<b>c</b>) women and men.</p>
Full article ">Figure 19
<p>Perceptual evaluation of images obtained in the process of pseudo-coloring the image in <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>d for the “Hot” and “Radar” palettes and the one proposed by the authors (“Own”): (<b>a</b>) women, (<b>b</b>) men, (<b>c</b>) women and men.</p>
Full article ">Figure 20
<p>Evaluation of the perceptibility of images obtained in the process of pseudo-coloring the image in <a href="#applsci-13-09496-f010" class="html-fig">Figure 10</a>f for the “Hot” and “Radar” palettes and proposed by the authors (“Own”): (<b>a</b>) women, (<b>b</b>) men, (<b>c</b>) women and men.</p>
Full article ">Figure 21
<p>Course of normalized contrast values for the YUV model.</p>
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<p>Course of normalized contrast values for the CIE RGB model.</p>
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<p>Course of normalized contrast values for the PAL/SECAM model.</p>
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21 pages, 4359 KiB  
Article
Joint Deployment Optimization of Parallelized SFCs and BVNFs in Multi-Access Edge Computing
by Ying Han, Junbin Liang and Yun Lin
Appl. Sci. 2023, 13(12), 7261; https://doi.org/10.3390/app13127261 - 18 Jun 2023
Cited by 2 | Viewed by 1230
Abstract
In multi-access edge computing (MEC) networks, parallelized service function chains (P-SFCs) can provide low-delay network services for mobile users by deploying virtualized network functions (VNFs) to process user requests in parallel. These VNFs are unreliable due to software faults and server failures. A [...] Read more.
In multi-access edge computing (MEC) networks, parallelized service function chains (P-SFCs) can provide low-delay network services for mobile users by deploying virtualized network functions (VNFs) to process user requests in parallel. These VNFs are unreliable due to software faults and server failures. A practical way to address this is to deploy idle backup VNFs (BVNFs) near these active VNFs and activate them when active VNFs fail. However, deploying BVNFs preempts server resources and decreases the number of accepted user requests. Thus, this paper proposes a reliability enhancement approach that uses BVNFs satisfying the delay requirement as active VNFs to form P-SFCs, which contributes to the delay reduction and reliability enhancement. Since the resource capacities of edge servers can only deploy a certain number of P-SFCs and BVNFs, establishing how to deploy the minimum number of P-SFCs and BVNFs to satisfy the delay and reliability requirements of mobile users and maximize the number of accepted user requests is a challenging problem. In this paper, we first model the dynamics of delay and reliability caused by VNF parallelization and BVNFs deployment, then formulate the joint deployment problem of P-SFCs and BVNFs. Next, we design an approximation algorithm to deploy critical VNFs and BVNFs on a target edge server and schedule the data traffic of user requests processed by P-SFCs. Experimental results based on real-world datasets show that our proposed algorithm outperforms two benchmark algorithms in terms of throughput, delay, reliability, and resource utilization. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>The MEC network. Basic settings: There are two user requests, <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mn>1</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mn>2</mn> </msub> </mrow> </semantics></math>, with two SFCs, i.e., <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>F</mi> <msub> <mi>C</mi> <mn>1</mn> </msub> <mo>〈</mo> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>1</mn> </msub> <mo>,</mo> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>2</mn> </msub> <mo>,</mo> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>3</mn> </msub> <mo>〉</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>F</mi> <msub> <mi>C</mi> <mn>2</mn> </msub> <mo>〈</mo> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>1</mn> </msub> <mo>,</mo> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>3</mn> </msub> <mo>〉</mo> </mrow> </semantics></math>. The source and destination nodes of these two user requests are <span class="html-italic">BS</span><sub>1</sub> and <span class="html-italic">BS</span><sub>2</sub> and <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo> </mo> <mi>and</mi> <mo> </mo> <mi>B</mi> <msub> <mi>S</mi> <mn>4</mn> </msub> </mrow> </semantics></math>, respectively. For user request <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mn>1</mn> </msub> </mrow> </semantics></math>, the <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> <mi>N</mi> <mi>F</mi> </mrow> <mn>1</mn> </msub> </mrow> </semantics></math> instance is deployed in edge server <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mn>1</mn> </msub> </mrow> </semantics></math>, with the <math display="inline"><semantics> <mrow> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>2</mn> </msub> </mrow> </semantics></math> instance and the <math display="inline"><semantics> <mrow> <mi>V</mi> <mi>N</mi> <msub> <mi>F</mi> <mn>3</mn> </msub> </mrow> </semantics></math> instance in edge server <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mn>2</mn> </msub> </mrow> </semantics></math>. Thus, user request <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mn>1</mn> </msub> </mrow> </semantics></math> can obtain the required network service by traversing the instances in the edge servers in order.</p>
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<p>The operation to calculate reliability. The reliability of any single VNF instance is 0.8. All feasible sets are sequentially sorted by the ID of edge servers in each column while ensuring that the elements in each row are unchanged. The overall reliability <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mrow> <mi>V</mi> <mi>N</mi> <msup> <mi>F</mi> <mrow> <mi>l</mi> <mo>,</mo> <mi>i</mi> </mrow> </msup> </mrow> </msub> </mrow> </semantics></math> of <math display="inline"><semantics> <mrow> <mi>V</mi> <mi>N</mi> <msup> <mi>F</mi> <mi>l</mi> </msup> </mrow> </semantics></math> on <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>F</mi> <msub> <mi>C</mi> <mi>i</mi> </msub> </mrow> </semantics></math> is the sum of the reliability of all feasible sets.</p>
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<p>(<b>a</b>) Split target sub-flows; (<b>b</b>) merge and split multiple sub-flows; (<b>c</b>) schedule the traffic of target sub-flow to candidate flow. In <a href="#applsci-13-07261-f003" class="html-fig">Figure 3</a>a, the sum of transmission and processing capacity of the target sub-flow and candidate flow is x and y, respectively.</p>
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<p>Explanation of the delay-reduction scheme in our algorithm.</p>
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<p>The operation to obtain all feasible sets and calculate reliability when we determine whether to deploy parallel VNF instances on target edge server <span class="html-italic">V5</span>. There are three edge servers [<span class="html-italic">V1, V2, V3</span>] in the comparison set and one edge server [<span class="html-italic">V4</span>] in the reliability set. We first replace the edge servers in the comparison set with <span class="html-italic">V5</span>, and then we replace the other edge servers with <span class="html-italic">V4</span>.</p>
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<p>Explanation of the reliability-enhancement scheme in our algorithm.</p>
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<p>(<b>a</b>) Average delay and average delay requirement of all accepted user requests when the number of users changes; (<b>b</b>) the number of VNF instances consisting of active VNF instances and BVNF instances and average VNF reliability provided by all active VNF instances of all accepted user requests when the number of users changes; (<b>c</b>) the average reliability provided by one VNF instance, all active VNF instances and all VNF instances of all accepted user requests when the number of users changes; (<b>d</b>) throughput when the number of users changes.</p>
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<p>(<b>a</b>) Throughput when the number of edge servers changes; (<b>b</b>) the number of VNF instances and VNF reliability of all accepted user requests when the number of edge servers changes; (<b>c</b>) the average reliability provided by one VNF instance, all active VNF instances and all VNF instances of all accepted user requests when the number of edge servers changes; (<b>d</b>) throughput when the number of edge servers changes.</p>
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<p>(<b>a</b>) Throughput when the number of VNFs in SFC changes; (<b>b</b>) the number of VNF instances and the VNF reliability of all accepted user requests when the number of VNFs in SFC changes; (<b>c</b>) the average reliability provided by one VNF instance, all active VNF instances and all VNF instances of all accepted user requests when the number of VNFs in SFC changes.</p>
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<p>(<b>a</b>) Throughput when the reliability of VNF in SFC changes; (<b>b</b>) the number of VNF instances and VNF reliability of all accepted user requests when the reliability of VNF in SFC changes; (<b>c</b>) the average reliability provided by one VNF instance, all active VNF instances and all VNF instances of all accepted user requests when the reliability of VNF in SFC changes.</p>
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19 pages, 607 KiB  
Article
Topology Duration Optimization for UAV Swarm Network under the System Performance Constraint
by Rui Zhou, Xiangyin Zhang, Deyu Song, Kaiyu Qin and Limei Xu
Appl. Sci. 2023, 13(9), 5602; https://doi.org/10.3390/app13095602 - 1 May 2023
Cited by 3 | Viewed by 1804
Abstract
Network topology construction plays an important role in the application of large-scale unmanned aerial vehicle (UAV) swarm. Current researches usually perform the topology construction in terms of criteria of nodes energy consumption, transmission delay and network throughput, etc. However, another important criterion, the [...] Read more.
Network topology construction plays an important role in the application of large-scale unmanned aerial vehicle (UAV) swarm. Current researches usually perform the topology construction in terms of criteria of nodes energy consumption, transmission delay and network throughput, etc. However, another important criterion, the stability of swarm network topology, which is much critical for dynamic scenarios, has not been fully considered. In this paper, a novel topology construction method for UAV swarm network based on the criterion of topology duration is proposed. Specially, the topology construction of swarm network is formulated as an optimization problem of maximizing the topology duration while satisfying the constraints of certain network throughput, end-to-end delay, and nodes energy consumption. Then, a novel Group Trend Similarity based double-head Clustering method(GTSC) is employed to solve this problem, in which group similarity of movement, intra- and inter-cluster distance, node forwarding delay, and energy strategy are comprehensively taken into account. The proposed method is effective when used to perform the network topology construction for UAV swarm, which is verified by the simulation results. Furthermore, in comparison with representative algorithms, the proposed GTSC method exhibits better performance on topology duration, network throughput, end-to-end delay and energy consumption balance especially in a large-scale swarm scenarios. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>An example of UAV swarm deployment.</p>
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<p>A schematic diagram for the universal set <math display="inline"><semantics> <mrow> <mi mathvariant="bold">G</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math> and typical topology <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="bold">G</mi> <mi>d</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.(<b>a</b>) The universal set of network topology <math display="inline"><semantics> <mrow> <mi mathvariant="bold">G</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>b</b>) a typical <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="bold">G</mi> <mi>d</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> based on topology design.</p>
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<p>Flow chart of the proposed GTSC method.</p>
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<p>The network topology of UAV swarm constructed based on the proposed GTSC method.</p>
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<p>Comparison of topology duration under various methods.</p>
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<p>Average end-to-end delay of swarm network constructed based on various methods.</p>
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<p>The total throughput of swarm network constructed based on various methods.</p>
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<p>Energy balance of swarm network constructed based on various methods.</p>
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<p>Algorithm convergence speed.</p>
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25 pages, 3653 KiB  
Article
Teletraffic Analysis of DoS and Malware Cyber Attacks on P2P Networks under Exponential Assumptions
by Natalia Sánchez-Patiño, Gina Gallegos-Garcia and Mario E. Rivero-Angeles
Appl. Sci. 2023, 13(7), 4625; https://doi.org/10.3390/app13074625 - 6 Apr 2023
Cited by 2 | Viewed by 1894
Abstract
Peer-to-peer (P2P) networks are distributed systems with a communication model in which no central authority governs the behavior of individual peers. These networks currently account for a considerable percentage of all bandwidth worldwide. However, this communication model also has a clear disadvantage: it [...] Read more.
Peer-to-peer (P2P) networks are distributed systems with a communication model in which no central authority governs the behavior of individual peers. These networks currently account for a considerable percentage of all bandwidth worldwide. However, this communication model also has a clear disadvantage: it has a multitude of vulnerabilities and security threats. The nature of the P2P philosophy itself means that there is no centralized server responsible for uploading, storing, and verifying the authenticity of the shared files and packets. A direct consequence of this is that P2P networks are a good choice for hackers for the spread of malicious software or malware in general since there is no mechanism to control what content is shared. In this paper, we present a mathematical model for P2P networks to study the effect of two different attacks on these systems, namely, malware and denial of service. To analyze the behavior of the cyber attacks and identify important weaknesses, we develop different Markov chains that reflect the main dynamics of the system and the attacks. Specifically, our model considers the case in which a certain number of nodes are infected with a cyber worm that is spread throughout the network as the file is shared among peers. This allows observation of the final number of infected peers when an initial number (we evaluate the system for from 1 to 14 initial nodes) of malicious nodes infect the system. For the DoS attack, our model considers the portion of peers that are unable to communicate and the average attack duration to study the performance degradation of such an attack. A two-pronged approach was used to study the impact of the attacks on P2P networks; the first focused only on the P2P network, and the second focused on the attacks and the network. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Flow chart for operation of the P2P network.</p>
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<p>Flow chart for the operation of the malware attack in the P2P network.</p>
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<p>Flow chart for the operation of the DoS attack in the P2P network.</p>
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<p>Markov chain of the basic P2P system.</p>
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<p>Markov chain of the infection process in a P2P system.</p>
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<p>Markov chain of the infection process in a P2P system with countermeasures.</p>
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<p>Markov chain of the P2P network under a DoS attack.</p>
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<p>Evolution in time of one realization of the number of leechers and seeds in the system.</p>
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<p>Evaluation in time of one realization of the number of healthy and infected leechers and seeds.</p>
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<p>Average number of healthy and infected peers under a malware attack for different values of <math display="inline"><semantics> <mi>γ</mi> </semantics></math>, <math display="inline"><semantics> <mi>η</mi> </semantics></math>, and <math display="inline"><semantics> <mi>λ</mi> </semantics></math>. (<b>a</b>) Variation of infected nodes and <math display="inline"><semantics> <mi>γ</mi> </semantics></math>. (<b>b</b>) Variation of infected nodes and <math display="inline"><semantics> <mi>θ</mi> </semantics></math>. (<b>c</b>) Variation of infected nodes and <math display="inline"><semantics> <mi>λ</mi> </semantics></math>.</p>
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<p>Average number of healthy and infected nodes for different numbers of initial malicious nodes, Ni, and efficiency of the countermeasures, PI.</p>
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<p>Time evolution of the P2P system with <math display="inline"><semantics> <mrow> <mi>δ</mi> <mo>=</mo> </mrow> </semantics></math> 5 nodes affected by the DoS attack.</p>
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25 pages, 7279 KiB  
Article
Performance and Scalability Analysis of SDN-Based Large-Scale Wi-Fi Networks
by Mohsin Ali, Ali Imran Jehangiri, Omar Imhemed Alramli, Zulfiqar Ahmad, Rania M. Ghoniem, Mohammed Alaa Ala’anzy and Romana Saleem
Appl. Sci. 2023, 13(7), 4170; https://doi.org/10.3390/app13074170 - 24 Mar 2023
Cited by 8 | Viewed by 2735
Abstract
The Software-Defined Networking (SDN) paradigm is one that is utilized frequently in data centers. Software-Defined Wireless Networking, often known as SDWN, refers to an environment in which concepts from SDN are implemented in wireless networks. The SDWN is struggling with challenges of scalability [...] Read more.
The Software-Defined Networking (SDN) paradigm is one that is utilized frequently in data centers. Software-Defined Wireless Networking, often known as SDWN, refers to an environment in which concepts from SDN are implemented in wireless networks. The SDWN is struggling with challenges of scalability and performance as a result of the growing number of wireless networks in its coverage area. It is thought that SDN techniques, such as Mininet-Wi-Fi and Ryu Controller for wireless networks, can overcome the problems with scalability and performance. Existing Wi-Fi systems do not provide SDN execution to end clients, which is one reason why the capability of Wi-Fi is restricted on SDN architecture. Within the scope of this study, we analyzed Wi-Fi networks operating on SDN using the Transmission Control Protocol (TCP) and User Datagram Protocol (UDP). By utilizing a testbed consisting of Ryu Controller and Mininet-Wi-Fi, we were able to test Wi-Fi over SDN and evaluate its performance in addition to its scalability. When evaluating the performance of a network, we take into account a number of different metrics, such as bandwidth, round-trip time, and jitter. In order to assess the level of performance, the SDN-based Wi-Fi controller Ryu is linked to an increasing number of access points (1, 2, 3, and 4) as well as stations (10, 30, 50, and 100). The experimental findings obtained using Mininet-Wi-Fi indicate the scalability and dependability of the network performance provided by the SDN Wi-Fi network controller Ryu in an SDN environment. In addition, the round-trip time for TCP packets grows proportionally with the number of hops involved. A single access point is capable of simultaneously supporting up to fifty people at once. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>The differences between an SDN switch and a traditional switch [<a href="#B17-applsci-13-04170" class="html-bibr">17</a>,<a href="#B20-applsci-13-04170" class="html-bibr">20</a>,<a href="#B39-applsci-13-04170" class="html-bibr">39</a>].</p>
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<p>SDN-based architecture.</p>
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<p>Simple topology.</p>
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<p>Mininet-Wi-Fi-created linear topology.</p>
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<p>Custom tree topology.</p>
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<p>TCP bandwidth for 1 access point.</p>
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<p>TCP bandwidth for 2 access points.</p>
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<p>TCP bandwidth for 3 access points.</p>
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<p>TCP bandwidth for 4 access points.</p>
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<p>UDP bandwidth for 1 access point.</p>
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<p>UDP bandwidth for 2 access points.</p>
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<p>UDP bandwidth for 3 access points.</p>
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<p>UDP bandwidth for 4 access points.</p>
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<p>UDP jitter for 1 access point.</p>
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<p>UDP jitter for 2 access points.</p>
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<p>UDP jitter for 3 access points.</p>
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<p>UDP jitter for 4 access points.</p>
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<p>Graph showing flow setup latency with three topologies.</p>
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<p>Graph showing flow setup latency.</p>
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15 pages, 3727 KiB  
Article
MAC-Based Compression Ratio Improvement for CAN Security
by Jinhui Piao, Shiyi Jin, Dong-Hyun Seo, Samuel Woo and Jin-Gyun Chung
Appl. Sci. 2023, 13(4), 2654; https://doi.org/10.3390/app13042654 - 18 Feb 2023
Cited by 2 | Viewed by 1571
Abstract
Information security in a controller area network (CAN) is becoming more important as the connections between a vehicle’s internal and external networks increase. Encryption and authentication techniques can be applied to CAN data frames to enhance security. To authenticate a data frame, a [...] Read more.
Information security in a controller area network (CAN) is becoming more important as the connections between a vehicle’s internal and external networks increase. Encryption and authentication techniques can be applied to CAN data frames to enhance security. To authenticate a data frame, a message authentication code (MAC) needs to be transmitted with the CAN data frame. Therefore, space for transmitting the MAC is required within the CAN frame. Recently, the Triple ID algorithm has been proposed to create additional space in the data field of the CAN frame. The Triple ID algorithm ensures every CAN frame is authenticated by at least 4 bytes of MAC without changing the original CAN protocol. However, since the Triple ID algorithm uses six header bits, there is a problem associated with low data compression efficiency. In this paper, we propose an algorithm that can remove up to 15 bits from frames compressed with the Triple ID algorithm. Through simulation using CAN signals of a Kia Sorento vehicle and an LS Mtron tractor, we show that the generation of frames containing compressed messages of 4 bytes or more is reduced by up to 99.57% compared to the Triple ID method. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>32-bit MAC of the Practical Security algorithm in CAN 2.0B.</p>
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<p>Header bit representation by modified MAC.</p>
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<p>MAC generation procedure of Triple ID algorithm.</p>
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<p>12-bit data representation using 4-byte MAC with the proposed method.</p>
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<p>Proposed data transmission flow chart.</p>
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<p>Proposed data reception flow chart.</p>
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<p>3-way handshake for the session keys (authentication key and encryption key).</p>
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<p>Peak load simulation using CANoe system.</p>
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28 pages, 27159 KiB  
Article
Number of Lines of Image Reconstructed from a Revealing Emission Signal as an Important Parameter of Rasterization and Coherent Summation Processes
by Ireneusz Kubiak, Artur Przybysz and Krystian Grzesiak
Appl. Sci. 2023, 13(1), 447; https://doi.org/10.3390/app13010447 - 29 Dec 2022
Cited by 1 | Viewed by 1157
Abstract
An important issue in the protection of information against electromagnetic penetration is the possibility of its non-invasive acquisition. In many cases, getting hold of protected information involves recreating and presenting it in a readable and understandable form. In particular, this applies to data [...] Read more.
An important issue in the protection of information against electromagnetic penetration is the possibility of its non-invasive acquisition. In many cases, getting hold of protected information involves recreating and presenting it in a readable and understandable form. In particular, this applies to data processed in graphic form and in such a form presented on the side of eavesdropping system. The effectiveness of reconstructing data in graphic form requires knowledge of raster parameters, i.e., the line length and the number of lines of the reproduced image. This article presents new measures allowing for the determination of the correct number of lines in an image. The maximum value of the measures has been proposed as a criterion for the correctness of determining the number of image lines. A predetermined number of image lines was assumed as the input data, which was determined on the basis of the analysis of the amplitude variability of the recorded revealing emission signal. The result of the considerations of the effectiveness of the measures adopted in the process of electromagnetic infiltration was the indication of methods that allow for the correct determination of the number of lines of the reproduced image. The correct number of image lines allows the use of the coherent summation algorithm of tens of images. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Surrounding us potential sources of undesirable emissions correlated with the information processed.</p>
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<p>An example of anechoic chamber.</p>
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<p>Illustrating the effect of the number lines of image on its content: (<b>a</b>) correct number lines of the image, (<b>b</b>) too few lines of the image, (<b>c</b>) too many lines of the image.</p>
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<p>The working scheme of coherent summing of images in electromagnetic infiltration process.</p>
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<p>Illustrating the influence of a wrongly determined number lines of image on the result of coherent summation (a summation of two first images): (<b>a</b>) for a small number lines of image, (<b>b</b>) for a large number lines of image.</p>
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<p>Examples of incorrectly determined number of lines of the reconstructed images: (<b>a</b>) too few lines, (<b>b</b>) correct number of lines, (<b>c</b>) too many lines—30-fold summation of the reconstructed image for the revealing emission signal measured at the frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, band reception <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, primary image displayed in the mode of 1280 × 1024/60 Hz, DVI standard, image in greyscale.</p>
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<p>Examples of incorrectly determined number of lines of the reconstructed images: (<b>a</b>) too few lines, (<b>b</b>) correct number of lines, (<b>c</b>) too many lines—30-fold summation of the reconstructed image for the revealing emission signal measured at the frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, band reception <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, primary image displayed in the mode of 1280 × 1024/60 Hz, DVI standard, image in greyscale.</p>
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<p>Test images used in the analysis of the effectiveness of the proposed measures in the process of determining the correct number of lines of the reproduced image: (<b>a</b>) a photo showing two vehicles (HDMI standard), (<b>b</b>) a three-column text (HDMI standard), (<b>c</b>) three words “protection” written in secure font (VGA standard), (<b>d</b>) menu of multifunctional device.</p>
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<p>Measuring systems for three different sources of revealing emissions: (<b>a</b>) HDMI and DVI standards, (<b>b</b>) display of laser printers.</p>
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<p>An algorithm for determining the correct number lines of a reconstructed image.</p>
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<p>Image reconstructed (two consecutive realizations of the image) from the recorded revealing signal for: (<b>a</b>) too few image lines, <math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>730</mn> </mrow> </semantics></math>; (<b>b</b>) correct number of image lines, <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>806</mn> </mrow> </semantics></math>; (<b>c</b>) too many image lines, <math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>900</mn> </mrow> </semantics></math>.</p>
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<p>Normalized values (in relation to the maximum value) of the variability of measures as a function of the number of image lines, supporting the determination of the correct number of lines of the image reproduced for the source image in the form of a picture from <a href="#applsci-13-00447-f007" class="html-fig">Figure 7</a>a—HDMI graphic standard, computer monitor operating mode 1280 × 1024/60 Hz, frequency of the reveal emission signal <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, reception bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, correct number of lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1066</mn> </mrow> </semantics></math>.</p>
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<p>Images reconstructed from the revealing emission signal measured at the frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math> for the number of lines of this image determined in accordance with the criterion of the maximum value of the measures presented in <a href="#applsci-13-00447-f011" class="html-fig">Figure 11</a>: (<b>a</b>) the number of image lines determined in accordance with method V (<math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>1062</mn> </mrow> </semantics></math>, the number of lines smaller than required), (<b>b</b>) number of image lines determined in accordance with methods I, II, III, IV, VI, and VII (<math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1066</mn> </mrow> </semantics></math>, correct number of lines).</p>
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<p>Normalized values (in relation to the maximum value) of the variability of measures as a function of the number of image lines, supporting the determination of the correct number of lines of the image reproduced for the source image in the form of a picture from <a href="#applsci-13-00447-f007" class="html-fig">Figure 7</a>b—HDMI graphic standard, computer monitor operating mode 1280 × 1024/60 Hz, frequency of the reveal emission signal <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>200</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, reception bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>100</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, correct number of lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1125</mn> </mrow> </semantics></math>.</p>
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<p>Images reconstructed from the revealing emission signal measured at the frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>200</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math> for the number of lines of this image determined in accordance with the criterion of the maximum value of the measures presented in <a href="#applsci-13-00447-f013" class="html-fig">Figure 13</a>: (<b>a</b>) the number of image lines determined in accordance with method V (<math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>1114</mn> </mrow> </semantics></math>, the number of lines smaller than required), (<b>b</b>) number of image lines determined in accordance with methods I, II, III, IV, VI, and VII (<math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1125</mn> </mrow> </semantics></math>, correct number of lines).</p>
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<p>Normalized values (in relation to the maximum value) of the variability of measures as a function of the number of image lines, supporting the determination of the correct number of lines of the image reproduced for the source image in the form of a picture from <a href="#applsci-13-00447-f007" class="html-fig">Figure 7</a>c—VGA graphic standard, computer monitor operating mode 1024 × 768/60 Hz, frequency of the reveal emission signal <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>558</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, reception bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, correct number of lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>806</mn> </mrow> </semantics></math>.</p>
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<p>Images reconstructed from the revealing emission signal measured at the frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>558</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, for the number of lines of this image determined in accordance with the criterion of the maximum value of the measures presented in <a href="#applsci-13-00447-f015" class="html-fig">Figure 15</a>: (<b>a</b>) the number of image lines determined in accordance with method V (<math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>803</mn> </mrow> </semantics></math>, the number of lines smaller than required), (<b>b</b>) number of image lines determined in accordance with method II (<math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>823</mn> </mrow> </semantics></math>, the number of lines bigger than required), (<b>c</b>) number of image lines determined in accordance with method I, III, IV, VI, and VII (<math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>806</mn> </mrow> </semantics></math>, correct number of lines).</p>
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<p>Normalized values (in relation to the maximum value) of the variability of measures as a function of the number of image lines, supporting the determination of the correct number of lines of the image reproduced for the source image in the form of a picture from <a href="#applsci-13-00447-f007" class="html-fig">Figure 7</a>d—menu of multifunctional device, frequency of the reveal emission signal <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>235</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, reception bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, correct number of lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>288</mn> </mrow> </semantics></math>.</p>
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<p>Images reconstructed from the revealing emission signal measured at the frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>235</mn> <mrow> <mo> </mo> <mi>MHz</mi> </mrow> </mrow> </semantics></math>, for the number of lines of this image determined in accordance with the criterion of the maximum value of the measures presented in <a href="#applsci-13-00447-f017" class="html-fig">Figure 17</a>: (<b>a</b>) the number of image lines determined in accordance with method V (<math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>273</mn> </mrow> </semantics></math>, the number of lines smaller than required), (<b>b</b>) number of image lines determined in accordance with method I, II, III, IV, VI, and VII (<math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>C</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>288</mn> </mrow> </semantics></math>, correct number of lines).</p>
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<p>Images for which statistical analyses were conducted (images reconstructed on base on reveal emissions for thirty times summation without colorization): (<b>a</b>) DVI standard, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>365</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>525</mn> </mrow> </semantics></math>, resolution 640 × 480/60 Hz; (<b>b</b>) DVI standard, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1066</mn> <mo>,</mo> </mrow> </semantics></math> resolution 1280 × 1024/60 Hz; (<b>c</b>) DVI standard, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1805</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>100</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1066</mn> </mrow> </semantics></math>, resolution 1280 × 1024/60 Hz; (<b>d</b>) DVI standard, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1775</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>100</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>1125</mn> </mrow> </semantics></math>, resolution 1920 × 1080/60 Hz; (<b>e</b>) laser printer HP M507, menu with icons, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>392</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>266</mn> </mrow> </semantics></math>; (<b>f</b>) VGA standard, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>450</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>20</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>628</mn> </mrow> </semantics></math>, resolution 800 × 600/60 Hz; (<b>g</b>) laser printer, menu with text, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>235</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>288</mn> </mrow> </semantics></math>; (<b>h</b>) DVI standard, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>740</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>628</mn> </mrow> </semantics></math>, resolution 1280 × 1024/60 Hz; and (<b>i</b>) display of terminal VoIP, receive frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>800</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>20</mn> <mo> </mo> <mi>MHz</mi> <mo>,</mo> </mrow> </semantics></math> number lines <math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>528</mn> </mrow> </semantics></math>.</p>
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21 pages, 920 KiB  
Article
Metrics-Based Comparison of OWL and XML for Representing and Querying Cognitive Radio Capabilities
by Yanji Chen, Mieczyslaw M. Kokar, Jakub Moskal and Kaushik R. Chowdhury
Appl. Sci. 2022, 12(23), 11946; https://doi.org/10.3390/app122311946 - 23 Nov 2022
Cited by 1 | Viewed by 1256
Abstract
Collaborative spectrum access requires wireless devices to perform spectrum-related tasks (such as sensing) on request from other nodes. Thus, while joining the network, they need to inform neighboring devices and/or the central coordinator of their capabilities. During the operational phase, nodes may request [...] Read more.
Collaborative spectrum access requires wireless devices to perform spectrum-related tasks (such as sensing) on request from other nodes. Thus, while joining the network, they need to inform neighboring devices and/or the central coordinator of their capabilities. During the operational phase, nodes may request other permissions from the the controller, like the opportunity to transmit according to the current policies and spectrum availability. To achieve such coordinated behavior, all associated devices within the network need a language for describing radio capabilities, requests, scenarios, policies, and spectrum availability. In this paper, we present a thorough comparison of the use of two candidate languages—Web Ontology Language (OWL) and eXtensible Markup Language (XML)—for such purposes. Towards this goal, we propose an evaluation method for automating quantitative comparisons with metrics such as precision, recall, device registration, and the query response time. The requests are expressed in both SPARQL Protocol and RDF Query Language (SPARQL) and XML Query Language (XQuery), whereas the device capabilities are expressed in both OWL and XML. The evaluation results demonstrate the advantages of using OWL semantics to improve the quality of matching results over XML. We also discuss how the evaluation method can be applicable to other scenarios where knowledge, datasets, and queries require richer expressiveness and semantics. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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Figure 1
<p>Problem scenarios—UML use case diagram.</p>
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<p>Visual representation of the evaluation process.</p>
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<p>Data flow diagram of the evaluation process with the notations.</p>
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<p>DeVISor architecture.</p>
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<p>Metrics evaluation results (<b>a</b>) Average recall comparison; (<b>b</b>) Average precision comparison; (<b>c</b>) Average F-Measure comparison; (<b>d</b>) Device registration time comparison; (<b>e</b>) Average query response time comparison.</p>
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39 pages, 22754 KiB  
Article
Measurements and Correctness Criteria for Determining the Line Length of the Data Image Obtained in the Process of Electromagnetic Infiltration
by Ireneusz Kubiak and Artur Przybysz
Appl. Sci. 2022, 12(20), 10384; https://doi.org/10.3390/app122010384 - 14 Oct 2022
Cited by 4 | Viewed by 1249
Abstract
The protection of information against electromagnetic penetration is one of the most important aspects related to the protection of information against its non-invasive acquisition. Compared to the activities of cybercriminals, the use of electromagnetic emissions in the electromagnetic infiltration process does not leave [...] Read more.
The protection of information against electromagnetic penetration is one of the most important aspects related to the protection of information against its non-invasive acquisition. Compared to the activities of cybercriminals, the use of electromagnetic emissions in the electromagnetic infiltration process does not leave any traces of activity, and the owner of the information is not aware of its loss. The most common activities of electromagnetic eavesdropping are related to the infiltration of emission sources, graphically revealing the processing of information using both analog and digital methods. This allows for the presentation of reconstructed data in the form of images. Correct display of the acquired information requires knowledge of raster parameters such as line length and the number of lines building the reconstructed image. Due to the lack of direct access to the intercepted device, knowledge in this field does not allow for the correct determination of the aforementioned parameters, and thus, for recreating an image that would contain legible and understandable data. Additionally, incorrect values of the parameters result in failure of further processing of the obtained image, e.g., by using a coherent summation of images. Therefore, it is necessary to propose a solution that will allow not so much to roughly define the raster parameters but to estimate them precisely. Moreover, it should enable the automation of the process after the implementation of an appropriate algorithm. The article proposes an algorithm for estimating the line length of the reconstructed image. The raster parameter estimated with the use of the algorithm allows for summarizing images several dozen times with a significant improvement in the image quality and readability of the data contained in it. The image summation algorithm is very often used as one of the main image processing methods in the electromagnetic infiltration process. Incorrect raster parameters often make coherent summation useless. The proposed algorithm for estimating the line length of the reconstructed image uses three methods of determining the line length of the image for a given accuracy. At the same time, criteria were indicated that must be met to determine the correct length of the image line for the assumed accuracy of estimation. Obtained results confirmed that the proposed methods and criteria are effective in the process of electromagnetic infiltration. These methods allow us to determine the line length of reconstructed images with accuracy up to 105. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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Figure 1
<p>Image reconstructed for the correct value of the line length (<b>b</b>), the line length value too large (<b>a</b>), the line length value too small (<b>c</b>).</p>
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<p>An operation mechanism of image reconstruction (raster).</p>
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<p>The reconstructed image (rasterized) in correct way, VGA interface signal as a source of reveal emission, 640 × 480/60 Hz mode, 62.5 MHz sampling rate, line length 1984.11007.</p>
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<p>The reconstructed image (rasterized) in incorrect way, VGA interface signal as a source of reveal emission, 640 × 480/60 Hz mode, 62.5 MHz sampling rate, line length 1985.</p>
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<p>The reconstructed image (rasterized) in incorrect way, VGA interface signal as a source of reveal emission, 640 × 480/60 Hz mode, 62.5 MHz sampling rate, line length 1985, summed 10 times.</p>
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<p>Image reconstructed by summing 30 images for the line length <math display="inline"><semantics> <mrow> <mi>d</mi> <mo>=</mo> <mn>1920.001</mn> </mrow> </semantics></math>.</p>
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<p>Images displayed on a computer monitor (<b>a</b>–<b>c</b>,<b>e</b>,<b>f</b>) or multifunction device display (<b>d</b>), which are the source of revealing emissions: (<b>a</b>) a photo showing the road along the bushes, (<b>b</b>) a photo of the inside of an anechoic chamber, (<b>c</b>) three words “protection”, letter size 36, Arial font, (<b>d</b>) letter signs written with four fonts Safe Symmetric, Arial, Safe Asymmetric, Times New Roman, (<b>e</b>) a sentence written in Arial font of various sizes of letters, (<b>f</b>) display screen (Configuration menu) of the multifunction device.</p>
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<p>The measuring system of revealing emission signals.</p>
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<p>Algorithm of the determining the correct line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> of the reconstructed image.</p>
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<p>Normalized values of changing of images contrasts calculated according to Equations (2), (8) and (11) in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for different accuracies Δ: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>, (<b>d</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math>, (<b>e</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math>, (<b>f</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>, original image <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a.</p>
Full article ">Figure 11
<p>Normalized values of changing of images contrasts calculated according to Equations (2), (8) and (11) in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for different accuracies Δ: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>, (<b>d</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math>, (<b>e</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math>, (<b>f</b>)<math display="inline"><semantics> <mrow> <mo> </mo> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>, original image <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d.</p>
Full article ">Figure 12
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1954.00000</mn> </mrow> </semantics></math>, multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1954.00000</mn> </mrow> </semantics></math>, image summation multiple <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math> —the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 13
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.70000</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 14
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.65000</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 15
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.64900</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 16
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.64890</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 17
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>a) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.64892</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.64893</mn> </mrow> </semantics></math> —multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 18
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>b) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1954.00000</mn> </mrow> </semantics></math>, multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1954.00000</mn> </mrow> </semantics></math>, image summation multiple <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math> —the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 19
<p>The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math> and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>b).</p>
Full article ">Figure 20
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>b) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>1334</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.64857</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1953.64858</mn> </mrow> </semantics></math> —multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 21
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>c) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>768</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3907.00000</mn> </mrow> </semantics></math>, image summation multiple <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3907.00000</mn> </mrow> </semantics></math>, multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math> —the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 22
<p>The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math> and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>c).</p>
Full article ">Figure 23
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>c) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>768</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3907.26019</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3907.26025</mn> </mrow> </semantics></math> —multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, HDMI standard.</p>
Full article ">Figure 24
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>740</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3300.00000</mn> </mrow> </semantics></math>, image summation multiple <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3300.00000</mn> </mrow> </semantics></math>, multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math> —the source of revealing signal emission—display monitor, VGA standard.</p>
Full article ">Figure 25
<p>The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d).</p>
Full article ">Figure 26
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>740</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3299.97000</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, VGA standard.</p>
Full article ">Figure 27
<p>The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d).</p>
Full article ">Figure 28
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>740</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3299.97050</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, VGA standard.</p>
Full article ">Figure 29
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>d) and (<b>b</b>) image reconstructed on the basis of the recorded revealing emission signal at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>740</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3299.97057</mn> </mrow> </semantics></math> (accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>)—multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, VGA standard.</p>
Full article ">Figure 30
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>e) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>450</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3303.00000</mn> </mrow> </semantics></math>, image summation multiple <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3300.00000</mn> </mrow> </semantics></math>, multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math> —the source of revealing signal emission—display monitor, VGA standard.</p>
Full article ">Figure 31
<p>The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math> and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>e).</p>
Full article ">Figure 32
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>e) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>450</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>50</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3303.22632</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>3303.22637</mn> </mrow> </semantics></math> —multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math>, the source of revealing signal emission—display monitor, VGA standard.</p>
Full article ">Figure 33
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>f) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>235</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1863.00000</mn> </mrow> </semantics></math>, image summation multiple <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1863.00000</mn> </mrow> </semantics></math>, multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math> —the source of revealing signal emission—display of laser printer.</p>
Full article ">Figure 34
<p>The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math> and (<b>d</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>f).</p>
Full article ">Figure 35
<p>(<b>a</b>) The normalized values of the adopted measures (method I, II and III) calculated in domain of image line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> </mrow> </semantics></math> for the accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math> (for the original image shown in <a href="#applsci-12-10384-f007" class="html-fig">Figure 7</a>f) and images reconstructed on the basis of the recorded revealing emission signals at frequency <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>o</mi> </msub> <mo>=</mo> <mn>235</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math> (receiving bandwidth <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>W</mi> <mo>=</mo> <mn>10</mn> <mo> </mo> <mi>MHz</mi> </mrow> </semantics></math>, accuracy <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mo>=</mo> <mn>0.00001</mn> </mrow> </semantics></math>), (<b>b</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1862.54155</mn> </mrow> </semantics></math> and (<b>c</b>) for estimated line length <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mi mathvariant="sans-serif">Δ</mi> </msub> <mo>=</mo> <mn>1862.54158</mn> </mrow> </semantics></math> —multiple of image summation <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>u</mi> <msub> <mi>m</mi> <mrow> <mi>M</mi> <mi>T</mi> <mi>L</mi> </mrow> </msub> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math>, the source of revealing signal emission—display of laser printer.</p>
Full article ">
10 pages, 1981 KiB  
Article
A Testbed for Investigating the Effect of Salinity and Turbidity in the Red Sea on White-LED-Based Underwater Wireless Communication
by Ayshah S. Alatawi
Appl. Sci. 2022, 12(18), 9266; https://doi.org/10.3390/app12189266 - 15 Sep 2022
Cited by 7 | Viewed by 2306
Abstract
Several industrial and scientific underwater applications require high-speed wireless connectivity. Acoustic communications have low data rates and high latency, whereas attenuation in seawater severely limits radio frequency communications. Optical wireless communication is a promising solution, with high transmission rates (up to Gb/s) and [...] Read more.
Several industrial and scientific underwater applications require high-speed wireless connectivity. Acoustic communications have low data rates and high latency, whereas attenuation in seawater severely limits radio frequency communications. Optical wireless communication is a promising solution, with high transmission rates (up to Gb/s) and little attenuation in water at visible wavelengths. This study explores the feasibility of white-LED-based underwater optical wireless communication (UWOC) by considering Red Sea parameters. High salinity is the most prominent attribute of the Red Sea that can affect underwater communication and requires investigation. Considering this, the received signal intensity fluctuation under increasing water salinity was experimentally investigated. In the same experiment, the impact of growing turbidity was tested, as it is the most influential parameter and tends to block the entire LED-based communication system with little increase. The experimental results show that the signals are affected less by salinity and more by turbidity but are found to be sufficiently strong to be used for communication in the Red Sea. Finally, it was concluded that a white LED is capable of sending data at the maximum possible salinity values of 40 g/L. However, the turbidity can significantly limit the transmission distance to less than 60 cm. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
Show Figures

Figure 1

Figure 1
<p>Salinity map.</p>
Full article ">Figure 2
<p>LED-based UWOC system, (<b>a</b>) block diagram, and (<b>b</b>) experimental testbed.</p>
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<p>Light communication transmitter circuit diagram.</p>
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<p>LM385 voltage measurement.</p>
Full article ">Figure 5
<p>Comparison of received power with different salinity at different transmission distances.</p>
Full article ">Figure 6
<p>Comparison of the received power with different turbidity at different transmission distances.</p>
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18 pages, 4787 KiB  
Article
Fourier and Chirp-Z Transforms in the Estimation Values Process of Horizontal and Vertical Synchronization Frequencies of Graphic Displays
by Ireneusz Kubiak and Artur Przybysz
Appl. Sci. 2022, 12(10), 5281; https://doi.org/10.3390/app12105281 - 23 May 2022
Cited by 4 | Viewed by 1701
Abstract
The electromagnetic protection of IT devices includes a number of organizational and technical measures aimed at ensuring control over radiated and conducted revealing emissions. This is of particular importance for ensuring information security in wireless communication and the processing of data presented in [...] Read more.
The electromagnetic protection of IT devices includes a number of organizational and technical measures aimed at ensuring control over radiated and conducted revealing emissions. This is of particular importance for ensuring information security in wireless communication and the processing of data presented in graphic form. In each of these cases, the occurring electromagnetic emissions pose the risk of a lack of electromagnetic immunity to the so-called eavesdropping process based on forming revealing emissions. Included in the elements of the security chain preventing electromagnetic eavesdropping on wireless communication and the devices building such systems are activities related to the determination of the Technical Device Security Level (TDSL) or its class. The above is related to the performance of electromagnetic emissions tests and identifying which of them must be treated as revealing emissions, which are only disturbances and do not threaten the security of the processed information. It is intuitively understandable that it is particularly important to ensure the security of interfaces that process video data. The nature of the electromagnetic emission signals generated by these interfaces means that the related information can be intercepted with the use of relatively simple methods, and under favorable circumstances even with the use of a receiving device not very technologically advanced. In the case of the electromagnetic safety assessment of video devices, common practice is therefore activities aimed at reconstructing information related to the video signal. This requires the parameters of the reconstructed image appropriate for the eavesdropped device operation mode and the conditions of recording the revealing emission signals to be determined. The article presents the results of works related to the analysis of the possibility of using spectral analysis methods (Fast Fourier FFT transform and Chirp-Z transform) to automate the process of determining the above-mentioned parameters in the case of reproducing images from emission signals recorded by using the ADC analog-to-digital converter. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Timing relationships between video signals and (<b>a</b>) horizontal and (<b>b</b>) vertical sync signals for VGA monitor (video graphics array) operating in 640 × 480/60 Hz mode.</p>
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<p>Test images: (<b>a</b>) 8 × 8 vertical stripes and (<b>b</b>) a window of MS Word editor.</p>
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<p>(<b>a</b>) Amplitude spectrum of the test signal (strips 8 × 8) and magnification of its fragments corresponding to the (<b>b</b>) horizontal and (<b>c</b>) vertical sync frequencies.</p>
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<p>(<b>a</b>) Amplitude spectrum of the test signal (window of MS Word editor) and magnification of its fragments corresponding to the (<b>b</b>) horizontal and (<b>c</b>) vertical sync frequencies.</p>
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<p>(<b>a</b>) Amplitude spectrum of the test signal (window of MS Word editor) and magnification of its fragments corresponding to the (<b>b</b>) horizontal and (<b>c</b>) vertical sync frequencies.</p>
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<p>Magnification of the fragments of the amplitude spectrum corresponding to the (<b>a</b>) horizontal and (<b>b</b>) vertical sync frequencies.</p>
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<p>The block diagram of the determining the Chirp-Z transform.</p>
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<p>A window of Raster Generator with an exemplary reconstructed image based on a recorded revealing signal.</p>
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<p>Rasterized images on base on test signals obtained from the BMP file after the differentiation operation: (<b>a</b>) strips 8 × 8 pixels-fragment, (<b>b</b>) window of MS Word editor.</p>
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<p>Images reconstructed as a result of 30-fold summation for the <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mi>H</mi> </msub> <mo> </mo> </mrow> </semantics></math>parameter defined for: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <msup> <mn>2</mn> <mrow> <mn>24</mn> </mrow> </msup> </mrow> </semantics></math> (<a href="#applsci-12-05281-t006" class="html-table">Table 6</a>), (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <msup> <mn>2</mn> <mrow> <mn>25</mn> </mrow> </msup> </mrow> </semantics></math> (<a href="#applsci-12-05281-t006" class="html-table">Table 6</a>), according to the FFT algorithm.</p>
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<p>The real test system used to measure revealing emissions.</p>
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16 pages, 5887 KiB  
Article
Implementation of a Noise-Shaped Signaling System through Software-Defined Radio
by Junsung Choi, Dongryul Park, Suil Kim and Seungyoung Ahn
Appl. Sci. 2022, 12(2), 641; https://doi.org/10.3390/app12020641 - 10 Jan 2022
Cited by 5 | Viewed by 1690
Abstract
Along with the development of electromagnetic weapons, Electronic Warfare (EW) has been rising as the future form of war. Especially in the area of wireless communications, high security defense systems such as Low Probability of Detection (LPD), Low Probability of Interception (LPI), and [...] Read more.
Along with the development of electromagnetic weapons, Electronic Warfare (EW) has been rising as the future form of war. Especially in the area of wireless communications, high security defense systems such as Low Probability of Detection (LPD), Low Probability of Interception (LPI), and Low Probability of Exploitation (LPE) communication algorithms are being studied to prevent military force loss. One LPD, LPI, and LPE communication algorithm, physical-layer security, has been discussed and studied. We propose a noise signaling system, a type of physical-layer security, which modifies conventionally modulated I/Q data into a noise-like shape. To suggest the possibility of realistic implementation, we use Software-Defined Radio (SDR). Since there are certain hardware limitations, we present the limitations, requirements, and preferences of practical implementation of the noise signaling system. The proposed system uses ring-shaped signaling, and we present a ring-shaped signaling system algorithm, SDR implementation methodology, and performance evaluations of the system using the metrics of Bit Error Rate (BER) and Probability of Modulation Identification (PMI), which we obtain by using a Convolutional Neural Network (CNN) algorithm. We conclude that the ring-shaped signaling system can perform high LPI/LPE communication functioning because an eavesdropper cannot obtain the correct modulation scheme information. However, the performance can vary with the configurations of the I/Q data-modifying factors. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Ring-shaped signaling system block diagram.</p>
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<p>I/Q constellation (<b>a</b>) before signaling process and (<b>b</b>) after ring-shaped signaling process.</p>
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<p>Phase-modifying factor generation process.</p>
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<p>Distribution of magnitude-modifying factor.</p>
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<p>Ring-shaped signaling processed I/Q constellation (<b>a</b>) only affected by phase-modifying factor and (<b>b</b>) only affected by magnitude-modifying factor.</p>
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<p>Block diagram of (<b>a</b>) carrier synchronizer function and (<b>b</b>) frequency offset estimator function.</p>
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<p>Transformation process of conventional bits to symbols.</p>
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<p>Proposed header and data separated symbol transformation process.</p>
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<p>Constellation of (<b>a</b>) QPSK original, (<b>b</b>) 16 QAM original, (<b>c</b>) 64 QAM original, (<b>d</b>) reshaped QPSK, (<b>e</b>) reshaped 16 QAM, and (<b>f</b>) reshaped 64 QAM.</p>
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<p>Constellation of (<b>a</b>) QPSK original, (<b>b</b>) 16 QAM original, (<b>c</b>) 64 QAM original, (<b>d</b>) reshaped QPSK, (<b>e</b>) reshaped 16 QAM, and (<b>f</b>) reshaped 64 QAM.</p>
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<p>BER simulation results (fixed <span class="html-italic">I<sub>p</sub></span> and varying <span class="html-italic">I<sub>m</sub></span>) for (<b>a</b>) QPSK, (<b>b</b>) 16QAM, and (<b>c</b>) 64QAM.</p>
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<p>SDR performance evaluation experiment set-up.</p>
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<p>BER comparison between theoretical values and SDR performance.</p>
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<p>I/Q constellation shapes of (<b>a</b>) QPSK, (<b>b</b>) 8 PSK, and (<b>c</b>) 16 PSK.</p>
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<p>Performance evaluations with varying (<b>a</b>) magnitude-modifying factors (<span class="html-italic">I<sub>m</sub></span>) and (<b>b</b>) phase-modifying factors (<span class="html-italic">I<sub>p</sub></span>).</p>
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<p>PMI accuracy table of constructed CNN algorithm.</p>
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<p>PMI evaluation with varying <span class="html-italic">I<sub>m</sub></span> and <span class="html-italic">I<sub>p</sub></span> = 1.</p>
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<p>PMI evaluation with varying <span class="html-italic">I<sub>m</sub></span> and <span class="html-italic">I<sub>p</sub></span> = 4.</p>
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13 pages, 864 KiB  
Article
Saddle Point Approximation of Mutual Information for Finite-Alphabet Inputs over Doubly Correlated MIMO Rayleigh Fading Channels
by Yuyu Liu, Jinbao Zhang and Dan Zhang
Appl. Sci. 2021, 11(10), 4700; https://doi.org/10.3390/app11104700 - 20 May 2021
Cited by 2 | Viewed by 2004
Abstract
Given the mutual information of finite-alphabet inputs cannot be calculated concisely and accurately over fading channels, this paper proposes a new method to calculate the mutual information. First, the applicability of the saddle point method is studied, and then the mutual information is [...] Read more.
Given the mutual information of finite-alphabet inputs cannot be calculated concisely and accurately over fading channels, this paper proposes a new method to calculate the mutual information. First, the applicability of the saddle point method is studied, and then the mutual information is estimated by the saddle point approximation method with known channel state information. Furthermore, we induce the expectation of mutual information over doubly correlated multiple-input multiple-output (MIMO) Rayleigh fading channels. The validity of the saddle point approximation method is verified by comparing the numerical results of the Monte Carlo method and the saddle point approximation method under different doubly correlated MIMO fading channel scenarios. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Comparison on MI calculated by Monte Carlo and saddle point approximation under different input types and correction parameters (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi mathvariant="normal">T</mi> </msub> <mo>=</mo> <msub> <mi>ρ</mi> <mi>R</mi> </msub> <mo>=</mo> <mi>ρ</mi> </mrow> </semantics></math>) over doubly correlated Rayleigh fading channel model.</p>
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<p>Comparison on MI calculated by Monte Carlo and saddle point approximation under different input types and correction parameters (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi mathvariant="normal">T</mi> </msub> <mo>=</mo> <msub> <mi>ρ</mi> <mi>R</mi> </msub> <mo>=</mo> <mi>ρ</mi> </mrow> </semantics></math>) over doubly correlated Rice fading channel model.</p>
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<p>Comparison on normalized MI calculated by Monte Carlo and saddle point approximation according to upper and lower bounds of <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> </mrow> </semantics></math> by (14) under different input types, correction parameters (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi mathvariant="normal">T</mi> </msub> <mo>=</mo> <msub> <mi>ρ</mi> <mi>R</mi> </msub> <mo>=</mo> <mi>ρ</mi> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>) over doubly correlated Rayleigh fading channel model (N<sub>T</sub> = N<sub>R</sub> = 2).</p>
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<p>Comparison on MI calculated by Monte Carlo and the lower bound of saddle point approximation method under different input types and correction parameters (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi mathvariant="normal">T</mi> </msub> <mo>=</mo> <msub> <mi>ρ</mi> <mi>R</mi> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>) over doubly correlated Rayleigh fading channel model.</p>
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24 pages, 3333 KiB  
Article
Spectrum Awareness for Cognitive Radios Supported by Radio Environment Maps: Zonal Approach
by Paweł Kaniewski, Janusz Romanik, Edward Golan and Krzysztof Zubel
Appl. Sci. 2021, 11(7), 2910; https://doi.org/10.3390/app11072910 - 24 Mar 2021
Cited by 15 | Viewed by 2270
Abstract
In this paper, we present the concept of the Radio Environment Map (REM) designed to ensure electromagnetic situational awareness of cognitive radio networks. The map construction techniques based on spatial statistics are presented. The results of field tests done for Ultra High Frequency [...] Read more.
In this paper, we present the concept of the Radio Environment Map (REM) designed to ensure electromagnetic situational awareness of cognitive radio networks. The map construction techniques based on spatial statistics are presented. The results of field tests done for Ultra High Frequency (UHF) range with different numbers of sensors are shown. Exemplary maps with selected interpolation techniques are presented. Control points where the signal from licensed users is correctly estimated are identified. Finally, the map quality is assessed, and the most promising interpolation techniques are selected. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>The idea of sharing radio spectrum between primary users (PUs) and secondary users (SUs).</p>
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<p>Deployment of the sensors and position of the TX Antenna.</p>
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<p>Exemplary maps constructed for selected interpolation techniques and various number of sensors (signal level in dBm): (<b>a</b>) 26 sensors—Nearest Neighbor (NN); (<b>b</b>) 20 sensors—Inverse Distance Weighting (IDW) p3; (<b>c</b>) 13 sensors—Kriging.</p>
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<p>RMSE (value in dB) for tests with 13, 20, and 26 sensors—lowest RMSE test case.</p>
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<p>RMSE in zones (value in dB) for Test_13a.</p>
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<p>RMSE in zones (value in dB) for Test_20c.</p>
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<p>RMSE in zones (value in dB) for Test_26a.</p>
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<p>Correct estimation ratio for selected interpolation techniques for lowest RMSE tests.</p>
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<p>The transmitting part of the testbed for UHF band.</p>
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<p>The receiving part of the testbed for UHF band.</p>
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13 pages, 1459 KiB  
Article
A Universal Low-Complexity Demapping Algorithm for Non-Uniform Constellations
by Hao Wang, Mingqi Li and Chao Wang
Appl. Sci. 2020, 10(23), 8572; https://doi.org/10.3390/app10238572 - 30 Nov 2020
Cited by 4 | Viewed by 2255
Abstract
A non-uniform constellation (NUC) can effectively reduce the gap between bit-interleaved coded modulation (BICM) capacity and Shannon capacity, which has been utilized in recent wireless broadcasting systems. However, the soft demapping algorithm needs a lot of Euclidean distance (ED) calculations and comparisons, which [...] Read more.
A non-uniform constellation (NUC) can effectively reduce the gap between bit-interleaved coded modulation (BICM) capacity and Shannon capacity, which has been utilized in recent wireless broadcasting systems. However, the soft demapping algorithm needs a lot of Euclidean distance (ED) calculations and comparisons, which brings great demapping complexity to NUC. A universal low-complexity NUC demapping algorithm is proposed in this paper, which creates subsets based on the quadrant of the two-dimensional NUC (2D-NUC) received symbol or the sign of the in-phase (I)/quadrature (Q) component of the one-dimensional NUC (1D-NUC) received symbol. ED calculations and comparisons are only carried out on the constellation points contained in subsets. To further reduce the number of constellation points contained in subsets, the proposed algorithm takes advantage of the condensation property of NUC and regards a constellation cluster containing several constellation points as a virtual point. Analysis and simulation results show that, compared with the Max-Log-MAP algorithm, the proposed algorithm can greatly reduce the demapping complexity of NUC with negligible performance loss. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>2D-256NUC and 1D-1024NUC designed for different CRs in ATSC 3.0. (<b>a</b>) 2D-256NUC designed for CR = 3/15; (<b>b</b>) 2D-256NUC designed for CR = 13/15; (<b>c</b>) 1D-1024NUC designed for CR = 3/15; (<b>d</b>) 1D-1024NUC designed for CR = 13/15.</p>
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<p>BICM system block diagram.</p>
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<p>The subsets of ED comparison to calculate LLR(<math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mn>6</mn> </msub> </mrow> </semantics></math>) when the received symbol is in the first quadrant. (<b>a</b>) Subsets of Max-Log-MAP algorithm; (<b>b</b>) Subsets obtained after some constellation points are removed.</p>
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<p>The subsets of ED comparison to calculate LLR(<math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) when the received symbol is in the first quadrant. (<b>a</b>) Subsets of Max-Log-MAP algorithm; (<b>b</b>) Subsets obtained after some constellation points are removed.</p>
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<p>The subset of ED calculation when the received symbol is in the first quadrant. (<b>a</b>) Subset before using condensation characteristic; (<b>b</b>) Subset after using condensation characteristic.</p>
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<p>BER Performance comparison of Max-Log-MAP, QCSR and SCSR algorithms over i.i.d Rayleigh channel. Results presented for 2D-256NUCs. (<b>a</b>) CR = 2/15; (<b>b</b>) CR = 6/15; (<b>c</b>) CR = 10/15; (<b>d</b>) CR = 13/15.</p>
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<p>BER Performance comparison of Max-Log-MAP and SCSR demapping algorithms over i.i.d Rayleigh channel. Results presented for 1D-1024NUCs. (<b>a</b>) CR = 2/15; (<b>b</b>) CR = 6/15; (<b>c</b>) CR = 10/15; (<b>d</b>) CR = 13/15.</p>
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16 pages, 1230 KiB  
Article
Detection of Misconfigured BYOD Devices in Wi-Fi Networks
by Jaehyuk Choi
Appl. Sci. 2020, 10(20), 7203; https://doi.org/10.3390/app10207203 - 15 Oct 2020
Cited by 5 | Viewed by 2293
Abstract
As Bring Your Own Device (BYOD) policy has become widely accepted in the enterprise, anyone with a mobile device that supports Wi-Fi tethering can provide an active wireless Internet connection to other devices without restriction from network administrators. Despite the potential benefits of [...] Read more.
As Bring Your Own Device (BYOD) policy has become widely accepted in the enterprise, anyone with a mobile device that supports Wi-Fi tethering can provide an active wireless Internet connection to other devices without restriction from network administrators. Despite the potential benefits of Wi-Fi tethering, it raises new security issues. The open source nature of mobile operating systems (e.g., Google Android or OpenWrt) can be easily manipulated by selfish users to provide an unfair advantage throughput performance to their tethered devices. The unauthorized tethering can interfere with nearby well-planned access points (APs) within Wi-Fi networks, which results in serious performance problems. In this paper, we first conduct an extensive evaluation study and demonstrate that the abuse of Wi-Fi tethering that adjusts the clear channel access parameters has strong adverse effects in Wi-Fi networks, while providing the manipulated device a high throughput gain. Subsequently, an online detection scheme diagnoses the network condition and detects selfish tethering devices by passively exploiting the packet loss information of on-going transmissions. Our evaluation results show that the proposed method accurately distinguishes the manipulated tethering behavior from other types of misbehavior, including the hidden node problem. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Illustration of the problem: a misbehaving unauthorized Wi-Fi tethering sets up the network in a managed multi-access point (AP) network.</p>
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<p>Adversary model: selfish behavior with Clear Channel Assessment (CCA) manipulation will not freeze its back-off counter even if other nodes are transmitting.</p>
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<p>(<b>a</b>) PHY capture effect allows a receiver to successfully capture the signal of interest (SoI) if its Tx power is sufficiently higher than the sum of interferences. (<b>b</b>) MIM (Message-In-Message) allows for a receiver to disengage from an ongoing packet reception, and engage in a new, stronger packet.</p>
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<p>AP Interference graph of two simulated topologies.</p>
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<p>Impact of selfish carrier sense on throughput of transport-layer protocols over various cellular backhaul link capacities <math display="inline"><semantics> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>l</mi> </mrow> </msub> </semantics></math> for tethering in two multi-AP topologies.</p>
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<p>Impact of launching tethering on a partial-overlapped channel.</p>
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<p>Throughput comparison with selfish configurations of the <math display="inline"><semantics> <mrow> <mi>C</mi> <msub> <mi>W</mi> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> parameter.</p>
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<p>Throughput gain of selfish carrier sensing over various cellular backhaul link capacities and AP densities.</p>
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<p>The dynamics of CUBIA toward three difference types of frame losses.</p>
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<p>Impact of selfish intensity on the performance of well-behaving nodes.</p>
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<p>Impact of <math display="inline"><semantics> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>l</mi> </mrow> </msub> </semantics></math> on detection time.</p>
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<p>Impact of the first alarm threshold <math display="inline"><semantics> <msub> <mi>θ</mi> <mrow> <mi>A</mi> <mi>S</mi> </mrow> </msub> </semantics></math> on detection time for UDP and TCP protocols with <math display="inline"><semantics> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>l</mi> </mrow> </msub> </semantics></math> = 20 Mbps.</p>
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<p>Impact of the second alarm threshold <math display="inline"><semantics> <msub> <mi>θ</mi> <mi>S</mi> </msub> </semantics></math> for the given <math display="inline"><semantics> <msub> <mi>θ</mi> <mrow> <mi>A</mi> <mi>S</mi> </mrow> </msub> </semantics></math> = 3 on detection time with <math display="inline"><semantics> <msub> <mi>B</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>l</mi> </mrow> </msub> </semantics></math> = 20 Mbps.</p>
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13 pages, 540 KiB  
Article
Adaptive Relay Selection Scheme by Using Compound Channel
by Yu-Jin Na, Won-Seok Lee, Min-Jae Paek, Hyoung-Kyu Song, Duckdong Hwang and Young-Hwan You
Appl. Sci. 2020, 10(16), 5614; https://doi.org/10.3390/app10165614 - 13 Aug 2020
Cited by 1 | Viewed by 1885
Abstract
As a cellular network of the fifth generation (5G) is commercialized, mobile devices and data throughput have rapidly increased. According to the spatial density for communication increases, the nodes of cell are overloaded. Therefore, the heterogeneous ultra dense network (UDN) is suggested. Furthermore, [...] Read more.
As a cellular network of the fifth generation (5G) is commercialized, mobile devices and data throughput have rapidly increased. According to the spatial density for communication increases, the nodes of cell are overloaded. Therefore, the heterogeneous ultra dense network (UDN) is suggested. Furthermore, the techniques for selecting a relay have been proposed in the Heterogeneous Net (HetNet). The relays are needed to improve communication performance and mitigate overload of nodes. In this paper, an adaptive relay selection scheme is proposed to obtain the diversity gain from multiple relays. To enhance the reliability of communication, the proposed scheme suggests a new algorithm considering outage probability and diversity gain of compound channel. Furthermore, the selected relays use an antenna selection algorithm to improve the channel capacity. Simulation results show that the proposed scheme improves the bit error rate (BER) and the data throughput. Full article
(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)
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<p>Two-hop MIMO relaying system.</p>
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<p>Flow chart of the proposed scheme.</p>
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<p>BER performance with 4 antennas</p>
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<p>BER performance with 8 antennas</p>
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