Kamal Eldahshan
Al-Azhar University, Mathematics and computer science, Faculty Member
Mobile Location-dependent services are popular services that the mobile environments support. Data caching is an effective technique that plays an important role in improving these services. In mobile environments, due to the limited... more
Mobile Location-dependent services are popular services that the mobile environments support. Data caching is an effective technique that plays an important role in improving these services. In mobile environments, due to the limited cache size of mobile devices, the cache replacement which is finding a suitable subset of items for eviction from cache becomes important. Most of the existing cache replacement schemes use the cost functions in the replacement operation. In this paper we propose a Predictable Markov based Cache Replacement (PMCR) scheme for Mobile Environments. The proposed scheme uses a markov model with cost function in the replacement operation. The key idea of the markov model is the prediction of future client locations by giving us the weight of visiting each location whose data is cached. Simulation results show that our approach improves the system performance compared to the existing schemes.
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Abstract — Remote user authentication plays the most fundamental procedure to identify the legitimate users of a web service on the Internet. In general, the password-based authentication mechanism provides the basic capability to prevent... more
Abstract — Remote user authentication plays the most fundamental procedure to identify the legitimate users of a
web service on the Internet. In general, the password-based authentication mechanism provides the basic capability to prevent unauthorized access. Since, many researchers have proposed a number of password based authentication schemes which rely on a single channel for authentication. However to achieve a better security, it is possible to engage multi-channels for authenticating users. In this paper, we propose an efficient one time password (OTP) based authentication protocol over a multi-channels architecture. Where, the proposed protocol employing the RC4-EA encryption method to encrypt the plain-OTP to cipher-OTP. Then, Quick Response Code (QR) code is used as a data container to hide this cipher-OTP. Also, the purpose of the protocol is to integrate a web based application with mobile-based technology to communicate with the remote user over a multi-channels authentication scheme. The main advantage of the proposed protocol is to highly secure the authentication system by preventing the OTP from eavesdropping attack. Also, by integrating a Web-based application with mobile-based technology as a multi-channels scheme; the proposed protocol helps to overcome many challenging attacks such as replay attack, DoS attack, man-in-the-middle (MITM) attack, real-time phishing (RTP) and other malware attacks.
Keywords-Authentication; Multi-Channel Authentication (MCA); Data hiding; Quick Response Code (QR) code; Encryption.
Call for Papers:
https://sites.google.com/site/ijcsis/
web service on the Internet. In general, the password-based authentication mechanism provides the basic capability to prevent unauthorized access. Since, many researchers have proposed a number of password based authentication schemes which rely on a single channel for authentication. However to achieve a better security, it is possible to engage multi-channels for authenticating users. In this paper, we propose an efficient one time password (OTP) based authentication protocol over a multi-channels architecture. Where, the proposed protocol employing the RC4-EA encryption method to encrypt the plain-OTP to cipher-OTP. Then, Quick Response Code (QR) code is used as a data container to hide this cipher-OTP. Also, the purpose of the protocol is to integrate a web based application with mobile-based technology to communicate with the remote user over a multi-channels authentication scheme. The main advantage of the proposed protocol is to highly secure the authentication system by preventing the OTP from eavesdropping attack. Also, by integrating a Web-based application with mobile-based technology as a multi-channels scheme; the proposed protocol helps to overcome many challenging attacks such as replay attack, DoS attack, man-in-the-middle (MITM) attack, real-time phishing (RTP) and other malware attacks.
Keywords-Authentication; Multi-Channel Authentication (MCA); Data hiding; Quick Response Code (QR) code; Encryption.
Call for Papers:
https://sites.google.com/site/ijcsis/
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Recently, mobile crowd sensing (MCS) is an important approach for collecting data from the participants in the urban streets. The main problem in collecting data process is how to cover all segments the street sides and select a minimal... more
Recently, mobile crowd sensing (MCS) is an important approach for collecting data from the participants in the urban streets. The main problem in collecting data process is how to cover all segments the street sides and select a minimal number of participants in each street segment that preserves the energy of the mobile devices and prolongs the MCS network lifetime. To solve this problem, a new flow coverage scheme is proposed to cover a specific street and achieve the coverage requirements. The proposed scheme is based on using a modified localization method that uses a minimal usage of GPS and utilizes the Zig-bee technology to communicate with the neighbor nodes and estimate the distance between nodes by using the Time of Arrival method. Experimental results by using a real data show that the proposed localization and coverage scheme can achieve high localization accuracy, reduce the usage of location sensors, and prove that the proposed street coverage scheme achieves the coverage requirements.
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Numerous network cyberattacks have been launched due to inherent weaknesses. Network intrusion detection is a crucial foundation of the cybersecurity field. Intrusion detection systems (IDSs) are a type of machine learning (ML) software... more
Numerous network cyberattacks have been launched due to inherent weaknesses. Network intrusion detection is a crucial foundation of the cybersecurity field. Intrusion detection systems (IDSs) are a type of machine learning (ML) software proposed for making decisions without explicit programming and with little human intervention. Although ML-based IDS advancements have surpassed earlier methods, they still struggle to identify attack types with high detection rates (DR) and low false alarm rates (FAR). This paper proposes a meta-heuristic optimization algorithm-based hierarchical IDS to identify several types of attack and to secure the computing environment. The proposed approach comprises three stages: The first stage includes data preprocessing, feature selection, and the splitting of the dataset into multiple binary balanced datasets. In the second stage, two novel meta-heuristic optimization algorithms are introduced to optimize the hyperparameters of the extreme learning machi...
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This research introduces a novel deep learning-based approach for anomaly identification in surveillance films. The suggested approach is built on a deep network that has been taught to recognise objects and human activity in films. The... more
This research introduces a novel deep learning-based approach for anomaly identification in surveillance films. The suggested approach is built on a deep network that has been taught to recognise objects and human activity in films. The technique was evaluated on five large-scale datasets from the real world, including UCF-Crime, XD-Violence, UBI-Fights, and CCTV-Fights, UCF-101, as well as on artificial datasets with various object sizes, appearances, and activity types. We extract features from video frames using a 3D-convolutional neural network (3D-CNN), followed by convolutional short-term memory (ConvLSTM), and then conduct classification and recognition based on these characteristics. The results demonstrate that, when compared to state-of-the-art approaches described in the comparison, the suggested method achieves high accuracy and AUC in both indoor and outdoor scenarios..
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Software design has a main impact in the quality of the software systems. Anti-patterns are shortcomings exist in the software designs and impact negatively software quality. Mobile applications (apps) with anti-patterns have bad quality... more
Software design has a main impact in the quality of the software systems. Anti-patterns are shortcomings exist in the software designs and impact negatively software quality. Mobile applications (apps) with anti-patterns have bad quality and short lifetime. Many empirical studies have assessed that the anti-patterns have a negative impact on change-proneness, fault-proneness, memory consumption and energy efficiency. In addition to that, many studies showed that there was an improvement in the user interface and memory performance of mobile apps when correcting Android anti-patterns. The aim of our research is choosing the suitable UML modeling environment to detect Mobile applications' anti-patterns via reverse engineering. So, in this research, first we present a comparative study between nine UML tools for determining the tools that have the functionality for (reverse, forward) engineering and have the ability for validating the model against the anti-patterns. Second, we apply our proposed method to generate the class diagram model of the apps through decoding the Java source code and detects the design anti-patterns in the model. For validating the proposed method, we applied it in twenty-nine Mobile apps which were downloaded from APKmirror. The proposed method detects and treats ten anti-patterns which have appeared 749 times in the twenty-nine apps.
Research Interests: Computer Science and Acm
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Smart manufacturers system is faced with the planning and scheduling production challenge to achieve high performance. This research regards flexible job shop scheduling as a sequential decision-making problem and deep reinforcement... more
Smart manufacturers system is faced with the planning and scheduling production challenge to achieve high performance. This research regards flexible job shop scheduling as a sequential decision-making problem and deep reinforcement learning-based Actor-Critic framework is proposed to cope with this problem. The proposed model can extract features from the input data using a convolutional network. In each optimal solution, we regard each operation of a job as a decision that contains information; and each decision as a function of five times in job processing which is classified using information from dispatch rules. For the learning by steps, we run a one-step actor-critic and improve the returns by repeated more steps. We compare different learning rates and discount factors with the generated returns to show the performance of decisions taken by the learning agent. Finally, we experiment proposed model on a case study and benchmark dataset with different values of random seeds to ensure the proposed model framework is more effective over a long time. The results indicate that our proposed model has more effective to solve Flexible job shop scheduling problems with big data set that has more than 100 jobs and 100 machines.
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Building professional and efficient systems by using user experience became one of the important research activities that focus on the interactions between products, applications, designers, and users. Unfortunately, using user experience... more
Building professional and efficient systems by using user experience became one of the important research activities that focus on the interactions between products, applications, designers, and users. Unfortunately, using user experience faces many problems. One of these problems is how to predict a user experience efficiently to build robust, effective, and flexible applications. To solve this problem, it is needed to design an optimal and efficient method for predicting user experience which includes behavior and emotions experiences. In this paper, a two-tier ranking scheme by using two multi-criteria decision making approaches is proposed. This proposed scheme considers a user experience as a sequence of executed actions or operations and it can predicate the most efficient user experience sequence of operations among a group of user experiences or experiences of individual users on a certain system or application. It uses the combination of two multi-criteria decision making a...
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In this paper, we approach the problem of detecting and diagnosing COVID-19 infections using multisource scan images including CT and X-ray scans to assist the healthcare system during the COVID-19 pandemic. Here, a computer-aided... more
In this paper, we approach the problem of detecting and diagnosing COVID-19 infections using multisource scan images including CT and X-ray scans to assist the healthcare system during the COVID-19 pandemic. Here, a computer-aided diagnosis (CAD) system is proposed that utilizes analysis of the CT or X-ray to diagnose the impact of damage in the respiratory system per infected case. The CAD was utilized and optimized by hyper-parameters for shallow learning, e.g., SVM and deep learning. For the deep learning, mini-batch stochastic gradient descent was used to overcome fitting problems during transfer learning. The optimal parameter list values were found using the naïve Bayes technique. Our contributions are (i) a comparison among the detection rates of pre-trained CNN models, (ii) a suggested hybrid deep learning with shallow machine learning, (iii) an extensive analysis of the results of COVID-19 transition and informative conclusions through developing various transfer techniques...
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Cloud computing is an advanced technology that offers types of assistance on requests. Because of the huge measure of requests got from cloud clients, all requests should be managed efficiently. Therefore, the task scheduling is critical... more
Cloud computing is an advanced technology that offers types of assistance on requests. Because of the huge measure of requests got from cloud clients, all requests should be managed efficiently. Therefore, the task scheduling is critical in cloud computing. The provision of computational resources in cloud is controlled by a cloud provider. It is necessary to design high-efficiency scheduling algorithms that are compatible with the corresponding computing paradigms. This paper introduces a new task scheduling method for cloud computing called an ameliorated Round Robin algorithm (ARRA). The proposed algorithm develops an optimal time quantum based on the average of task burst time using fixed and dynamic manners. The experimental results showed that the ARRA significantly outperformed other algorithms including improved RR, enhanced RR, dynamic time quantum approach (ARR) and enhanced RR (RAST ERR) in terms of the average waiting time, average turnaround time and response time.
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Rapid advances in deep learning models have made it easier for public and crackers to generate hyper-realistic deepfake videos in which faces are swapped. Such deepfake videos may constitute a significant threat to the world if they are... more
Rapid advances in deep learning models have made it easier for public and crackers to generate hyper-realistic deepfake videos in which faces are swapped. Such deepfake videos may constitute a significant threat to the world if they are misused to blackmail public figures and to deceive systems of face recognition. As a result, distinguishing these fake videos from real ones has become fundamental. This paper introduces a new deepfake video detection method. You Only Look Once (YOLO) face detector is used to detect faces from video frames. A proposed hybrid method based on proposing two different feature extraction methods is applied to these faces. The first feature extraction method, a proposed Convolution Neural Network (CNN), is based on the Histogram of Oriented Gradient (HOG) method. The second one is an ameliorated XceptionNet CNN. The two extracted sets of features are merged together and fed as input to a sequence of Gated Recurrent Units (GRUs) to extract the spatial and t...
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Nowadays chaos theory related to cryptography has been addressed widely, so there is an intuitive connection between group key agreement and chaotic maps. Such a connector may lead to a novel way to construct authenticated and efficient... more
Nowadays chaos theory related to cryptography has been addressed widely, so there is an intuitive connection between group key agreement and chaotic maps. Such a connector may lead to a novel way to construct authenticated and efficient group key agreement protocols. Many chaotic maps based two-party/three-party password authenticated key agreement (2PAKA/3PAKA) schemes have been proposed. However, to the best of our knowledge , no chaotic maps based group (N-party) key agreement protocol without using a timestamp and password has been proposed yet. In this paper, we propose the first chaotic maps-based group authentication key agreement protocol. The proposed protocol is based on chaotic maps to create a kind of signcryption method to transmit authenticated information and make the calculated consumption and communicating round restrict to an acceptable bound. At the same time our proposed protocol can achieve members' revocation or join easily, which not only refrains from con...
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Security attacks become daily news due to an exposure of a security threat in a widely used software. Taking software security into consideration during the analysis, design, and implementation phases is a must. A software application... more
Security attacks become daily news due to an exposure of a security threat in a widely used software. Taking software security into consideration during the analysis, design, and implementation phases is a must. A software application should be protected against any security threat such as unauthorized distribution or code retrieval. Due to the lack of applying a software security standard architecture, developers may create software that may be vulnerable to many types of security threats. This paper begins by reviewing different types of known software security threats and their countermeasure mechanisms. Then, it proposes a new security optimization architecture for software applications. This architecture is a step towards establishing a standard to guarantee the software's security. Furthermore, it proposes an adapted software security optimization architecture for mobile applications. Besides, it presents an algorithmic implementation of the newly proposed architecture, th...
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Abstract — Mobile Location-dependent services are popular services that the mobile environments support. Data caching is an effective technique that plays an important role in improving these services. In mobile environments, due to the... more
Abstract — Mobile Location-dependent services are popular services that the mobile environments support. Data caching is an effective technique that plays an important role in improving these services. In mobile environments, due to the limited cache size of mobile devices, the cache replacement which is finding a suitable subset of items for eviction from cache becomes important. Most of the existing cache replacement schemes use the cost functions in the replacement operation. In this paper we propose a Predictable Markov based Cache Replacement (PMCR) scheme for Mobile Environments. The proposed scheme uses a markov model with cost function in the replacement operation. The key idea of the markov model is the prediction of future client locations by giving us the weight of visiting each location whose data is cached. Simulation results show that our approach improves the system performance compared to the existing schemes.<br>Keywords - Mobile Location-dependent services; Data dissemination; Cache replacement; Predicted region; Markov model; PMCR.<br>
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The amount of videos over the internet and media storage systems has dramatically increased. This poses challenges in video content understanding and management. A video is a complex and resource consuming media. In addition, efficient... more
The amount of videos over the internet and media storage systems has dramatically increased. This poses challenges in video content understanding and management. A video is a complex and resource consuming media. In addition, efficient use of video data requires the data to be understood and accessed without having to watch it entirely. For those reasons, video summarization (VS) has been a hot topic of recent researches. VS is the process of creating a compact representation that can provide the user with concise information about the video content. VS helps in efficient storage, quick browsing, and retrieval of video data maintaining its main features. In video codec and streaming contexts, Scalable Video Coding (SVC) enables dynamic adaptation based on network conditions and device capabilities. This paper reviews the recent work on scalable video summarization (SVS) and discusses its role in current research directions.
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With the fast advancement of wireless networks bandwidth and mobile devices, large scale digital video library systems are growing rapidly. However, the huge increasing of content and the data intensive nature of video make the management... more
With the fast advancement of wireless networks bandwidth and mobile devices, large scale digital video library systems are growing rapidly. However, the huge increasing of content and the data intensive nature of video make the management and browsing of video collections, as well as their search and retrieval, increasingly difficult. The need of having a media digital library is essential these days with intelligent tools for indexing the video with allocating the suitable metadata that describe the content of such videos and at the mean while tools for retrieving the archived video with fast techniques. These will be achieved across 3 steps, working on the stream coding with multi bit rates and methods of handling, representing the video with summarized stream carrying the same information of the full stream and deriving a media digital library for indexing and retrieval process. The first step, stream handling, will be across implementing scalable video techniques which set the b...
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Designing a user experience is a critical issue for building professional and efficient systems. The user experience introduces new research activities that focused on the interactions between products, applications, designers, and users.... more
Designing a user experience is a critical issue for building professional and efficient systems. The user experience introduces new research activities that focused on the interactions between products, applications, designers, and users. To achieve specific user experience goals, we need to find an optimal model for representing this user experience which includes behavior and emotions experiences in efficient and helpful way. In this paper, we propose a mathematical activity- based model for describing user experience including his behavior and emotions experiences by using category theory elements. This model describes any user behavior as an activity that consists of a set of actions and operations where their existence is based on a set of conditions. Also, we introduce a conditional category model that uses this activity representation by modifying category theory based on conditional criteria. This new model is presented as an efficient tool for representing user experience a...
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The massive volume of videos is highly demanding for produce an efficient and effective video indexing and retrieving frameworks. Extracting and representation of visual features plays a significant role in the video/image retrieval and... more
The massive volume of videos is highly demanding for produce an efficient and effective video indexing and retrieving frameworks. Extracting and representation of visual features plays a significant role in the video/image retrieval and computer vision. This paper proposes a new compact descriptor named Global Dominant Scale Invariant Feature Transform (GD-SIFT). The GD-SIFT requires fewer bits (16 bits) to represent each visual feature. Importantly, the proposed descriptor is vocabulary-free, training-free and suitable for online and real-time applications. Also, this paper proposes a new video indexing and retrieving framework based on the proposed GD-SIFT descriptor. The proposed framework is a content-based video indexing and retrieving, which helps to retrieve videos by text (e.g. Video name or metadata), image (video frame) or video clip. The experiments carried out on the standard Stanford I2V dataset. Our experiments demonstrated that, the GD-SIFT descriptor is more efficien...
The International Journal of Computer Science and Information Security (IJCSIS) is a refereed, international publication featuring the latest research findings and industry solutions involving all aspects of computing and security. The... more
The International Journal of Computer Science and Information Security (IJCSIS) is a refereed, international publication featuring the latest research findings and industry solutions involving all aspects of computing and security. The editorial board is pleased to present the June 2015 issue. The purpose of this edition is to disseminate experimental and theoretical research from both industry and academia in the broad areas of Computer Science, ICT & Security and further bring together people who work in the relevant areas. As the editors of this issue, we are glad to see variety of articles focusing on the major topics of innovation and computer science; computer security, interdisciplinary applications, information technologies etc. This journal promotes excellent research publications which offer significant contribution to the computer science knowledge and which are of high interest to a wide academic/research/practitioner audience.
Over the last five years, we have witnessed significant growth of IJCSIS in several key areas, include the expansion of scope to recruit papers from emerging areas of green & sustainable computing, cloud computing security, forensics, mobile computing and big data analytics. IJCSIS archives all publications in major academic/scientific databases and is indexed by the following International agencies and institutions: Google Scholar, CiteSeerX, Cornell’s University Library, Ei Compendex, Scopus, DBLP, DOAJ, ProQuest, ArXiv, ResearchGate and EBSCO.
We are indebted to the wonderful team of publication staff members, associate editors, and reviewers for their dedicated services to select and publish extremely high quality papers for publication in IJCSIS. In particular, I would like to thank all associate editors who have answered the frequent calls to process the papers assigned to them in a timely fashion. I would also like to thank the authors for submitting their high quality papers to IJCSIS and the readers for continued support to IJCSIS by citing papers published in IJCSIS. Without their continued and unselfish commitments, IJCSIS would not have achieved its current premier status.
We support researchers to succeed by providing high visibility & impact value, prestige and efficient publication process & service.
For further questions please do not hesitate to contact us at ijcsiseditor@gmail.com.
A complete list of journals can be found at:
http://sites.google.com/site/ijcsis/
IJCSIS Vol. 13, No. 6, June 2015 Edition
ISSN 1947-5500 © IJCSIS, USA.
Over the last five years, we have witnessed significant growth of IJCSIS in several key areas, include the expansion of scope to recruit papers from emerging areas of green & sustainable computing, cloud computing security, forensics, mobile computing and big data analytics. IJCSIS archives all publications in major academic/scientific databases and is indexed by the following International agencies and institutions: Google Scholar, CiteSeerX, Cornell’s University Library, Ei Compendex, Scopus, DBLP, DOAJ, ProQuest, ArXiv, ResearchGate and EBSCO.
We are indebted to the wonderful team of publication staff members, associate editors, and reviewers for their dedicated services to select and publish extremely high quality papers for publication in IJCSIS. In particular, I would like to thank all associate editors who have answered the frequent calls to process the papers assigned to them in a timely fashion. I would also like to thank the authors for submitting their high quality papers to IJCSIS and the readers for continued support to IJCSIS by citing papers published in IJCSIS. Without their continued and unselfish commitments, IJCSIS would not have achieved its current premier status.
We support researchers to succeed by providing high visibility & impact value, prestige and efficient publication process & service.
For further questions please do not hesitate to contact us at ijcsiseditor@gmail.com.
A complete list of journals can be found at:
http://sites.google.com/site/ijcsis/
IJCSIS Vol. 13, No. 6, June 2015 Edition
ISSN 1947-5500 © IJCSIS, USA.