Recent Advances in Security, Privacy and Trust for Internet-of-Things (IoT) and Cyber-Physical Systems (CPS)
- Available for pre-order. Item will ship after December 17, 2020
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, 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.
This book on Recent Advances in Security, Privacy and Trust for Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) will discuss and present techniques and methodologies as well 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.
- Introduces new directions for research, development, and engineering security, privacy, and trust of IoT and Cyber-Physical Systems.
- Includes 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.
It 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.
Table of Contents
An Overview of the Integration Between Cloud Computing and Internet of things (IoT) Technologies
Cyber-Physical Systems in Healthcare – Review of Architecture, Security Issues, Intrusion Detection and Defenses
The Future of Privacy and Trust on the Internet of Things (IoT) for Healthcare: Concepts, Challenges, and Security Threat Mitigations
Towards the Detection and Mitigation of Ransomware Attacks in Medical Cyber-Physical Systems (MCPSs)
Security Challenges and Requirements for Industrial IoT Systems
Network Intrusion Detection with XGBoost
Anomaly Detection on Encrypted and High-performance Data Networks by means of Machine Learning Techniques
Deep Learning for Network Intrusion Detection: An Empirical Assessment
SPATIO: end-uSer Protection AgainsI IoT Intrusions
Low Power Physical Layer Security Solutions for IoT Devices
Some Research Issues of Harmful and Violent Content Filtering for Social Networks in the Context of Large-Scale and Streaming Data with Apache Spark
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.