The Internet of Things (IoT) has emerged due to information and communication technology developments, expanding the ability to connect numerous objects. The wide range of facilities enabled by IoT has generated a vast amount of data, making cybersecurity an imperative requirement for personal safety and for ensuring the sustainability of IoT itself. This book covers security and privacy research in the IoT domain, compiling technical and management approaches, addressing real-world problems, and providing practical advice to the industry. The book includes a collection of high-quality research works covering key emerging trends in IoT security and privacy that span the entire IoT architecture layers, focusing on different critical IoT applications such as advanced metering infrastructure and smart grids, smart locks, and cyber-physical systems. The provided state-of-the-art body of knowledge is essential for researchers, practitioners, postgraduate students, and developers interested in the security and privacy of the IoT paradigm, IoT-based systems, and any related research discipline. The book is a valuable companion and comprehensive reference for postgraduate and possibly some senior undergraduate students taking an advanced IoT security and privacy course.

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.

This book is a relevant reference for any readers interested in the security aspects of Cyber-Physical Systems and particularly useful for those looking to keep informed on the latest advances in this dynamic area. Cyber-Physical Systems (CPSs) are characterized by the intrinsic combination of software and physical components. Inherent elements often include wired or wireless data communication, sensor devices, real-time operation and automated control of physical elements. Typical examples of associated application areas include industrial control systems, smart grids, autonomous vehicles and avionics, medial monitoring and robotics. The incarnation of the CPSs can therefore range from considering individual Internet-of-Things devices through to large-scale infrastructures. Presented across ten chapters authored by international researchers in the field from both academia and industry, this book offers a series of high-quality contributions that collectively address and analyze the state of the art in the security of Cyber-Physical Systems and related technologies. The chapters themselves include an effective mix of theory and applied content, supporting an understanding of the underlying security issues in the CPSs domain, alongside related coverage of the technological advances and solutions proposed to address them. The chapters comprising the later portion of the book are specifically focused upon a series of case examples, evidencing how the protection concepts can translate into practical application.

This book is a relevant reference for any readers interested in the security aspects of Cyber-Physical Systems and particularly useful for those looking to keep informed on the latest advances in this dynamic area. Cyber-Physical Systems (CPSs) are characterized by the intrinsic combination of software and physical components. Inherent elements often include wired or wireless data communication, sensor devices, real-time operation and automated control of physical elements. Typical examples of associated application areas include industrial control systems, smart grids, autonomous vehicles and avionics, medial monitoring and robotics. The incarnation of the CPSs can therefore range from considering individual Internet-of-Things devices through to large-scale infrastructures. Presented across ten chapters authored by international researchers in the field from both academia and industry, this book offers a series of high-quality contributions that collectively address and analyze the state of the art in the security of Cyber-Physical Systems and related technologies. The chapters themselves include an effective mix of theory and applied content, supporting an understanding of the underlying security issues in the CPSs domain, alongside related coverage of the technological advances and solutions proposed to address them. The chapters comprising the later portion of the book are specifically focused upon a series of case examples, evidencing how the protection concepts can translate into practical application.

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.

This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition.

This book provides the reader with a comprehensive selection of cutting-edge algorithms, technologies, and applications. The volume offers new insights into a range of fundamentally important topics in network architectures, network security, and network applications. It serves as a reference for researchers and practitioners by featuring research contributions exemplifying research done in the field of network systems. In addition, the book highlights several key topics in both theoretical and practical aspects of networking. These include wireless sensor networks, performance of TCP connections in mobile networks, photonic data transport networks, security policies, credentials management, data encryption for network transmission, risk management, live TV services, and multicore energy harvesting in distributed systems.

This volume presents recent research in cyber security and reports how organizations can gain competitive advantages by applying the different security techniques in real-world scenarios. The volume provides reviews of cutting-edge technologies, algorithms, applications and insights for bio-inspiring cyber security-based systems. The book will be a valuable companion and comprehensive reference for both postgraduate and senior undergraduate students who are taking a course in cyber security. The volume is organized in self-contained chapters to provide greatest reading flexibility.

This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition.

This volume presents recent research in cyber security and reports how organizations can gain competitive advantages by applying the different security techniques in real-world scenarios. The volume provides reviews of cutting edge technologies, algorithms, applications and insights for bio-inspiring cyber security-based systems. The book will be a valuable companion and comprehensive reference for both postgraduate and senior undergraduate students who are taking a course in cyber security. The volume is organized in self-contained chapters to provide greatest reading flexibility."

This book constitutes the refereed proceedings of the International Conference on Advances in Security of Information and Communication Networks, Sec Net 2013, held in Cairo, Egypt, in September 2013. The 21 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on networking security; data and information security; authentication and privacy; security applications.

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The rapid advancements in telecommunications, computing hardware and software, and data encryption, and the widespread use of electronic data processing and electronic business conducted through the Internet have led to a strong increase in information security threats. The latest advances in information security have increased practical deployments and scalability across a wide range of applications to better secure and protect our information systems and the information stored, processed and transmitted. This book outlines key emerging trends in information security from the foundations and technologies in biometrics, cybersecurity, and big data security to applications in hardware and embedded systems security, computer forensics, the Internet of Things security, and network security. Information Security: Foundations, technologies and applications is a comprehensive review of cutting-edge algorithms, technologies, and applications, and provides new insights into a range of fundamentally important topics in the field. This up-to-date body of knowledge is essential reading for researchers and advanced students in information security, and for professionals in sectors where information security is required.