Magdy Bayoumi

This book provides a comprehensive treatment of security in the widely adopted, Radio Frequency Identification (RFID) technology. The authors present the fundamental principles of RFID cryptography in a manner accessible to a broad range of readers, enabling them to improve their RFID security design. This book also offers the reader a range of interesting topics portraying the current state-of-the-art in RFID technology and how it can be integrated with today’s Internet of Things (IoT) vision. The authors describe a first-of-its-kind, lightweight symmetric authenticated encryption cipher called Redundant Bit Security (RBS), which enables significant, multi-faceted performance improvements compared to existing cryptosystems. This book is a must-read for anyone aiming to overcome the constraints of practical implementation in RFID security technologies.

This book provides a comprehensive treatment of security in the widely adopted, Radio Frequency Identification (RFID) technology. The authors present the fundamental principles of RFID cryptography in a manner accessible to a broad range of readers, enabling them to improve their RFID security design. This book also offers the reader a range of interesting topics portraying the current state-of-the-art in RFID technology and how it can be integrated with today’s Internet of Things (IoT) vision. The authors describe a first-of-its-kind, lightweight symmetric authenticated encryption cipher called Redundant Bit Security (RBS), which enables significant, multi-faceted performance improvements compared to existing cryptosystems. This book is a must-read for anyone aiming to overcome the constraints of practical implementation in RFID security technologies.

This book explores how artificial intelligence, cloud computing, and edge technologies are transforming video streaming systems. It delves into AI-driven adaptive bitrate streaming, predictive resource allocation, and federated learning for personalized recommendations. The integration of cloud and edge computing is highlighted as a solution for scalability and low-latency streaming, addressing challenges like bandwidth optimization, cost-efficiency, and Quality of Experience (QoE). The book offers actionable insights into emerging technologies like 5G, quantum computing, and blockchain. It features case studies and real-world implementations, making it an essential resource for researchers, industry professionals, and students. Bridging theory and practice, the book provides a comprehensive guide to building the next generation of efficient and scalable video streaming infrastructures.

This book discusses the design and evaluation of Physically Unclonable Functions (PUFs) that are suitable for securing highly energy constrained devices, while at the same time classifying the many applications and devices that would benefit from various PUF designs.

This book introduces a novel transcoding algorithm for real time video applications, designed to overcome inter-operability problems between MPEG-2 to H.264/AVC. The new algorithm achieves 92.8% reduction in the transcoding run time at a price of an acceptable Peak Signal-to-Noise Ratio (PSNR) degradation, enabling readers to use it for real time video applications. The algorithm described is evaluated through simulation and experimental results. In addition, the authors present a hardware implementation of the new algorithm using Field Programmable Gate Array (FPGA) and Application-specific standard products (ASIC).• Describes a novel transcoding algorithm for real time video applications, designed to overcome inter-operability problems between H.264/AVC to MPEG-2; • Implements algorithm presented using Field Programmable Gate Array (FPGA) and Application-specific Integrated Circuit (ASIC);• Demonstrates the solution to real problems, with verification through simulation and experimental results.

This book introduces resource aware image decomposition, registration, fusion, object detection and tracking algorithms along with their applications in security, monitoring and integration in 3rd Generation Surveillance Systems. All algorithms are evaluated through experimental and simulation results and a parallel and pipelined efficient architecture for implementing the algorithms is described.

This book describes a communication paradigm that could shape the future of wireless communication networks, Opportunistic Spectrum Access (OSA) in Cognitive Radio Networks (CRN). While several theoretical OSA approaches have been proposed, they are challenged by the practical limitations of cognitive radios: the key enabling technology of OSA. This book presents an unprecedented formulation of the OSA problem in CNR that takes into account the practical limitations encountered due to existing technologies. Based on such a problem formulation, this book presents a framework and protocol details implementing the analytically-optimized solution of this problem. Unlike the state-of-the-art of CRN implementations that typically target software define radios which are not suitable for real systems, this book describes the implementation of distributed OSA, using practical radio transceiver technologies. It provides a thorough characterization of the gains available to theoretical OSA approaches if the practical limitations are taken into consideration. Tackles the cognitive radio networks performance optimization problem, taking into account the practical limitations of today’s technologies; Provides thorough performance evaluation in arbitrary, large-scale networks, as well as microscopic, small-scale performance evaluation, using realistic hardware implementation;Presents an empirical study of the gains available over existing techniques by adopting practical approaches;Tackles the cognitive radio networks performance optimization problem, taking into account the practical limitations of today’s technologies; Provides thorough performance evaluation in arbitrary, large-scale networks, as well as microscopic, small-scale performance evaluation, usingrealistic hardware implementation;Presents an empirical study of the gains available over existing techniques by adopting practical approaches;

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.

This book introduces resource aware image decomposition, registration, fusion, object detection and tracking algorithms along with their applications in security, monitoring and integration in 3rd Generation Surveillance Systems. All algorithms are evaluated through experimental and simulation results and a parallel and pipelined efficient architecture for implementing the algorithms is described.

This book describes a communication paradigm that could shape the future of wireless communication networks, Opportunistic Spectrum Access (OSA) in Cognitive Radio Networks (CRN). While several theoretical OSA approaches have been proposed, they are challenged by the practical limitations of cognitive radios: the key enabling technology of OSA. This book presents an unprecedented formulation of the OSA problem in CNR that takes into account the practical limitations encountered due to existing technologies. Based on such a problem formulation, this book presents a framework and protocol details implementing the analytically-optimized solution of this problem. Unlike the state-of-the-art of CRN implementations that typically target software define radios which are not suitable for real systems, this book describes the implementation of distributed OSA, using practical radio transceiver technologies. It provides a thorough characterization of the gains available to theoretical OSA approaches if the practical limitations are taken into consideration. Tackles the cognitive radio networks performance optimization problem, taking into account the practical limitations of today’s technologies; Provides thorough performance evaluation in arbitrary, large-scale networks, as well as microscopic, small-scale performance evaluation, using realistic hardware implementation;Presents an empirical study of the gains available over existing techniques by adopting practical approaches;Tackles the cognitive radio networks performance optimization problem, taking into account the practical limitations of today’s technologies; Provides thorough performance evaluation in arbitrary, large-scale networks, as well as microscopic, small-scale performance evaluation, usingrealistic hardware implementation;Presents an empirical study of the gains available over existing techniques by adopting practical approaches;

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.