Recent Advances in Security, Privacy, and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS)

Security, privacy, and trust in the Internet of Things (IoT) and CPS (Cyber-Physical Systems) are different from conventional security as concerns revolve around the collection and aggregation of data or transmission of data over the network. Analysis of cyber-attack vectors and the provision of appropriate mitigation techniques are essential research areas for these systems. Adoption of best practices and maintaining a balance between ease of use and security are, again, crucial for the effective performance of these systems.

Recent Advances in Security, Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS) discusses and presents techniques and methodologies, as well as a wide range of examples and illustrations, to effectively show the principles, algorithms, challenges, and applications of security, privacy, and trust for IoT and CPS.

Book features:

• Introduces new directions for research, development, and engineering security, privacy, and trust of IoT and CPS
• Includes a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges, and applications
• Covers most of the important security aspects and current trends not present in other reference books

This book will also serve as an excellent reference in security, privacy, and trust of IoT and CPS for professionals in this fast-evolving and critical field. The chapters present high-quality contributions from researchers, academics, and practitioners from various national and international organizations and universities.

Preface. Acknowledgment. Contributors. Chapter 1 An Overview of the Integration between Cloud Computing and Internet of Things (IoT) Technologies. Chapter 2 Cyber-Physical Systems in Healthcare: Review of Architecture, Security Issues, Intrusion Detection, and Defenses. Chapter 3 The Future of Privacy and Trust on the Internet of Things (IoT) for Healthcare: Concepts, Challenges, and Security Threat Mitigations. Chapter 4 Toward the Detection and Mitigation of Ransomware Attacks in Medical Cyber-Physical Systems (MCPSs). Chapter 5 Security Challenges and Requirements for Industrial IoT Systems. Chapter 6 Network Intrusion Detection with XGBoost. Chapter 7 Anomaly Detection on Encrypted and High-Performance Data Networks by Means of Machine Learning Techniques. Chapter 8 Deep Learning for Network Intrusion Detection: An Empirical Assessment. Chapter 9 SPATIO: end-uSer Protection Against IoT IntrusiOns. Chapter 10 Low Power Physical Layer Security Solutions for IoT Devices. Chapter 11 Some Research Issues of Harmful and Violent Content Filtering for Social Networks in the Context of Large-Scale and Streaming Data with Apache Spark. Index.

Kuan-Ching Li is a Professor in the Dept. of Computer Science and Information Engineering at Providence University, Taiwan; Brij B. Gupta is affiliated with the National Institute of Technology Kurukshetra, Haryana, India; Dharma P. Agrawal is OBR Distinguished Professor at t he University of Cincinnati.