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Full Description
The Internet of Things (IoT) concept has emerged partly due to information and communication technology developments and societal needs, 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 the IoT ecosystem. 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. This book also includes a collection of 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. This book is a valuable companion and comprehensive reference for postgraduate and senior undergraduate students taking an advanced IoT security and privacy course.
Contents
1. Cybersecurity Risk Assessment in Advanced Metering Infrastructure. 2. A Generative Neural Network for Improving Metamorphic Malware Detection in IoT Mobile Devices. 3. A Physical-Layer Approach for IoT Information Security During Interference Attacks. 4. Policy-Driven Security Architecture for Internet of Things (IoT) Infrastructure. 5. A Privacy-Sensitive, Situation-Aware Description Model for IoT. 6. Protect the Gate: A Literature Review of the Security and Privacy Concerns and Mitigation Strategies Related to IoT Smart Locks. 7. A Game-Theoretic Approach to Information Availability in IoT Networks. 8. Review on Variants of Restricted Boltzmann Machines and Autoencoders for Cyber-Physical Systems. 9.Privacy-Preserving Analytics of IoT Data Using Generative Models
