Steganalysis

We propose a steganalytic algorithm for triangle meshes, based on the supervised training of a classifier by discriminative feature vectors. After a normalization step, the triangle mesh is calibrated by one step of Laplacian smoothing and then a feature vector is computed, encoding geometric information corresponding to vertices, edges and faces. For a given steganographic or watermarking algorithm, we create a training set containing unmarked meshes and meshes marked by that algorithm, and train a classifier using Quadratic Discriminant Analysis. The performance of the proposed method was evaluated on six well-known watermarking/steganographic schemes with satisfactory accuracy rates.

Blind image steganalysis (BIS) is the process of detecting whether an input image has hidden data or not, without any prior known information ( i.e., blind) on the applied steganography technique. Recent BIS approaches typically suffer from limited detection accuracy and higher computational cost due to, e.g., pre-processing. In this paper, the proposed BIS approach discards the pre-processing step, so that the computational cost is reduced. As well, significant modifications on a recent convolution neural network (CNN)-model are considered in order to enhance the detection accuracy. First, an efficient parameters initialization is considered. Second, a cyclic learning rate and the LReLU activation function are used, during the learning phase, for faster convergence with noticeably higher detection accuracy. Finally, a hybrid technique of model and data parallelism techniques is performed in both convolution and fully connected layers, respectively, thus significantly reducing the c...

introduced in 2003, is a techniques used for hidden communication between two covert parties. It is an art of hidden communication. It also relates to the areas like network protocols and security for practical data hiding in communication networks using Transmission Control Protocol/Internet Protocol (TCP/IP). The typical steganographic method utilizes digitized media files (images, video and audio files) as a cover medium for hiding data, network steganography uses communication protocols such as TCP/IP. Such methods make it harder to detect and eliminate. In a typical steganography using network the modification of a single network protocol occurs. Such modification can be applied to the Protocol Data Unit. Network steganography sheltersa broad spectrum of techniques.

During the last decades, Steganography has found many applications. Many steganographic systems have been developed and used in various areas, e.g., in digital assets (DRM), Telecommunications, Medicine etc. In this paper, we prove that the set CF, which is a union of a certain set of Fibonacci numbers and a certain set of Catalan numbers, satisfies conditions, similar to those of Zeckendorf's Theorem. Therefore, it can be used for the encoding of data. Using this result, we propose a method that improves the Fibonacci data hiding technique.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Analyse de canaux de communication dans un contexte non coopératif. Johann Barbier

—This paper presents a keystroke dynamics system for mobile devices that employs a statistical distance-to-median anomaly detector. The selected feature set combines the keystroke timing features of hold and latency and the touch screen features of pressure and finger area. The proposed system consists of two modules: training and testing. The aim of the system is to be a research tool to serve two purposes: (i) the generation of a model-independent dataset of keystroke data on mobile devices, for comparison of keystroke dynamics anomaly detectors; (ii) to be used in the evaluation of the authentication performance of the implemented distance-to-median anomaly detector. The system works in the Android environment on Nexus smartphones and tablets. The experimental work has generated a dataset of 2856 records from 56 subjects, 51 records per subject, where each record represents 71 feature elements resulting from the typing of a standard 10-character password. Statistical analysis of the collected dataset showed an equal-error-rate (EER) of 0.049 when using a different pass-mark per subject, and 0.054 when using a global pass-mark for all subjects. The EER results are much lower than previously published results using three distance-based verification models. Also, the false-acceptance-rate at 5% false-rejection-rate is 5.6%, which is much lower than previously published results, but it is still high and needs to be reduced. Evaluation of the testing (authentication) part of the system was carried out through test runs where a genuine user enters his user-id and password as a login attempt, and the resulting test vector of feature elements are matched against the stored template of the user. The login attempt is classified as genuine or impostor based on a preset pass-mark. Conclusions and suggestions for future work are presented.

Özet: Tarih boyunca, insanoğlu toplumsal dokunun gelişmesi ile bilgi alışverişi için birçok yöntem kullanmıştır. Sosyal hayatın gelişmesi, ülkeler arasındaki siyasal ve toplumsal ilişkilerin önemini arttırmıştır. Toplumlar arasındaki iletişim yöntemlerinde, kaynak ve hedef arasında yol alan verinin önem derecesi farklılık göstermiştir. Değerli bilginin iletim ve depolanması için Kriptografi ve Steganografi gibi yöntemler geliştirilmiştir. Kriptografi, çeşitli şifreleme algoritmaları ile iletilecek verinin şifrelenmesidir. Şifrelenen verinin içeriğine ancak hedefin veriyi deşifre etmesi ile mümkündür. Steganografi veri içinde veri mantığı ile geliştirilmiş bir kavramdır. Taşınan veri içinde ulaştırılmak istenen bir başka veri gizlilik esasına göre iletilir. Steganografi yapısal anlamda dilbilimi ve teknik Steganografi şeklinde sınıflandırılır. Dilbilimi açısından bakıldığında, metin içinde bulunan eksik ya da boşluklardan ziyade, doğrudan cümle yapısı ve kelimelerle bağlantılıdır. Teknik Steganografi ise görüntü ve ses dosyaları aracılığı ile yapılan veri gizleme olaylarında ise kullanılmayan ve önemsiz bitler aracılığı ile veri gizlemesi yapılır. Bu çalışmada teknik steganografi alanında kullanılan algoritmalar araştırılarak, steganaliz yöntemlerinin verimlilikleri incelenmiştir. Anahtar Sözcükler-Veri gizleme, bilgi güvenliği, steganografi, steganaliz Abstract: Throughout history, human beings have a social status with the development of many methods used for the exchange of information. The development of social life, the importance of political and social relations between countries has increased. A method of communication between communities in the path between the source and destination of the data has shown that differ in severity. Cryptography and Steganography methods such as the transmission and storage of valuable information have been developed. Cryptography, various encryption algorithms to encrypt data to be transmitted with; but the goal is to decode the encrypted data on the content of the data is possible. Steganography is a concept that works with the logic data in data. Moved on the basis of the data desired to be delivered within the privacy of another data is transmitted. Steganography and technical Steganography in the form of structural linguistics in the sense are classified. From the perspective of Linguistics in the text, missing, or gaps, rather than directly linked to the sentence structure and words. Technical data hiding via steganography image and audio files in the event of data with unused bits of junk and to hide. In this study, the algorithms used in the field of technical steganography are investigated and the efficiency of the steganalysis methods are investigated.

A new steganography scheme using a reference image is proposed with two variants. In the first kind, secret text bits are directly embedded into the cover image after encryption using a reference image. In the second variant secret text is written/printed on a white canvas and then that image containing the secret text is converted into binary (BW) image. Any image could be used as a cover image. A special reference image will act as an encryption key and it is assumed that the used reference image is known to sender and receiver apriori. For a grayscale reference image, any k LSB bit planes could be used to encode the secret binary image bits before embedding them into k LSBs of the cover image. When k=1, the dimension of the secret image becomes the same as that of the reference image and cover image. With k=2, secret binary image size could be doubled or two secret images could be hidden using two LSB bit planes of the reference image and embedding them into two LSB bits of each cover image pixel. Any reversible mechanism could be used for encoding. Here XOR operation will be used for experiments. Two distinct advantages of this generic scheme are (i) It is far more secure than other image steganography techniques as adversary may know the encoding formulae , may collect the stego image but could not get information about the reference image used and which and how many bit planes are used for encoding as there could be millions of images and many combinations of bit planes that could have been employed; (ii) As the secret text is printed and then converted into an image, it overcomes one of the main limitations of LSB image steganography, i.e. robustness to random noise. Even with corrupted Stego image, the extracted binary image becomes corrupted too but most of the secret are still readable.
This scheme has lower capacity than the capacity that would have been achieved by directly embedding the secret text binary as in the first variant, but this could be overcome by using k>=2 as k=2 doubles the capacity. This whole scheme is generic and any digital media could be used as reference or cover. Experimental results demonstrate the robustness of the second variant against random noise, and standard image quality metrics such as MSE, PSNR, SSIM are evaluated and compared between the two variants.

The process of jumbling up the contents of a secret message so as to secure it, is known as cryptography, whereas the process of hiding the very existence of a secret message is known as steganography. The term "steganography" describes the method by which the contents of a secret message are concealed inside some other medium, so as to avoid any kind of detection by an intruder. In this paper, we have proposed two new approaches wherein both cryptography and steganography are used to encrypt the data and also to conceal these encrypted contents in some other medium. In the first method proposed, we have secured an image by converting it into an encrypted text using S-DES algorithm and a secret key and then concealing this encrypted text in some other image, whereas in the second method, we have secured an image directly by encrypting it using S-DES algorithm and an image key. The contents thus obtained are concealed inside another image so as to hide its very existence. Both these techniques have been tested and it has been observed that they prevent the possibilities of steganalysis also.

Steganisis is used to detect or extract hidden information. It is a set of techniques: visual or statistical, through which it is possible to verify the existence of steganography content. The preservation and role tools important in saving time and without providing angles of action for analysts; for image file analysis, such as StegDetect and StegExpose tools are able to do a mass analysis using steganographic methods attacks in a timely manner. When steganalistic methods and tools are combined intelligently, they are able to produce even more accurate results, which is paramount for important evidence to be perceived and collected. Using a qualitative methodology with an analytical character through a case study, major characteristics, tools and analyzes were analyzed through steganography exams.

A esteganálise é usada para detectar ou extrair informações ocultas. É um conjunto de técnicas: visual ou estatística, através das quais é possível verificar a existência de conteúdo de esteganografia. As ferramentas de esteganálise desempenham um papel importante na economia de tempo e no fornecimento de novos ângulos de atuação para analistas forenses; para análise em arquivos de imagens, as ferramentas StegDetect e StegExpose são capazes de fazer análise em massa usando ataques aos métodos esteganográficos em tempo eficiente. Quando os métodos e ferramentas esteganalíticas são combinados inteligentemente, eles são capazes de gerar resultados ainda mais precisos, o que é primordial para que importantes evidências sejam percebidas e coletadas. Utilizando uma metodologia qualitativa com caráter analítico por meio de estudo de caso, foram analisadas as principais características destas ferramentas, cujos resultados obtidos demonstram que elas podem ser grandes aliadas para o exame pericial de informações esteganográficas.

This study presents a new alternative of steganalysis method in order to detect hidden messages in text steganalysis called Evolution Detection Steganalysis System (EDSS) based on the evolution algorithm approach under Java Genetic Algorithms Package (JGAP). The result of the EDSS can be divided into two groups based on fitness values which are good fitness and bad fitness. Hopefully, this study can produce a good idea to other researchers for understanding the text steganalysis in order to develop a steganalysis system that can contribute a better performance in other domains.

Since people use internet daily they have to take care about information security requirement more and more. In this wok a new algorithm for RGB based images steganography is presented. The algorithm uses LSB principle for hiding a variable number of secret message bits in RGB 24-bits color image carrier either in other one or two channels depending on the third one (index channel). The algorithm offered good capacity ratio with no visual distortion on the original image after hiding the secret message. Histograms of three channels (red, green, blue) are also compared before and after hiding process.

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Embedding a message in media files, also known as steganography, is a common approach to hide secret information. It has been exploited by some criminals to confidentially exchange messages. As a countermeasure , tools have been developed in order to detect hidden information form digital media such as text, image, audio or video files. However the efficiency and performance of previous approaches still have room for improvement. In this research, we focus on algorithm design for better efficiency of hidden message detection from PNG files. We employ three classic AI approaches including neural network, fuzzy logic, and genetic algorithm and evaluate their efficiency and performance in controlled experiments. Finally we introduce our message detection system for PNG files based on LSB approach and present its usability in different case scenarios.

Steganalysis means analysis of stego images. Like cryptanalysis, steganalysis is used to detect messages often encrypted using secret key from stego images produced by steganography techniques. Recently lots of new and improved steganography techniques are developed and proposed by researchers which require robust steganalysis techniques to detect the stego images having minimum false alarm rate.
This paper discusses about the different Steganalysis techniques and help to understand how, where and when this techniques can be used based on different situations.

Digital watermarking [1] is the act of hiding information in multimedia data, for the purposes of content protection or authentication. In ordinary digital watermarking, the secret information is embedded into the multimedia data (cover data) with minimum distortion of the cover data. Due to these watermarking techniques the watermark image is almost negligible visible.
In this paper we will discuss about various techniques of Digital Watermarking techniques in spatial and frequency domains

Today, in the world of communication, connected systems is growing at a rapid pace. To accommodate this growth the need for computational power and storage is also increasing at a similar rate. Companies are investing a large amount of resources in buying, maintaining and ensuring availability of the system to their customers. To mitigate these issues, cloud computing is playing a major role [1]. The underlying concept of cloud computing dates back to the ‘50s but the term entering into widespread usage can be traced to 2006 when Amazon.com announced the Elastic Compute Cloud. In this paper, we will discuss about cloud security approaches. We have used the term “Cloud-Drain” to define data leakage in case of security compromise.

Steganalysis is an anti-steganography method aiming to detect secret message’s presence that is embedded inside an innocent looking medium. Usually, some steganalysis technique cannot be used universally because it is developed in order to detect secret message’s presence that’s embedded using a certain steganography technique. Therefore, blind steganalysis has become an interisting research area because it has the ability to detect secret message’s presence regardless of the steganography technique used in the process. In this research, a literature study is conducted to explains the concept behind how blind steganalysis works, the advantages and disadvantages of blind steganalysis, along with the illustration and comparison of some feature and classifier used in some blind steganalysis technique that have been proposed in previous researches. Our conclusion is that generally, blind steganalysis can be done through two phases: feature analysis and pattern classifier. Both phases can be done using numerous variant of feature and classifier. Blind steganalysis accuracy varied between 86% to 99.37%. The accuracy itself depends on the feature and classifier being used. Other than that, the more complex steganography algorithm encountered, the less accurate blind steganalysis will become

This paper presents study about how to hide the useful information and give the superficial knowledge of Steganography, compare encryption, and cryptography. This paper describes the present, past and future of Steganography. In this paper, we introduce Steganalysis for computer forensic investigation. Digital forensics is helpful in investigation of the cyber-crime and computer crime. With the help of Steganalysis, it detect the hide message which is transfer in the network. Furthermore, we have described the security system classification.