Intelligent Security Solutions for Cyber-Physical Systems

This book provides a comprehensive overview of cyber-physical systems and the security concepts like attack detection methods, system failures, risk identification, and management. It further elaborates on different machine-learning approaches to detect anomalous data from sensors, reinforcement learning, and time-series clustering.

A cyber-physical system (CPS) is a computer system in which a mechanism is controlled or monitored by computer-based algorithms and involves transdisciplinary approaches, merging theories of cybernetics, mechatronics, design, and process science. This text mainly concentrates on offering a foundational theoretical underpinning, and a comprehensive and coherent review of intelligent security solutions for cyber-physical systems. Features: Provides an overview of cyber-physical systems (CPSs) along with security concepts like attack detection methods, cyber-physical systems failures, and risk identification and managementShowcases cyber-physical systems (CPSs) security solutions, lightweight cryptographic solutions, and CPS forensics, etcEmphasizes machine learning methods for behavior-based intrusion detection in cyber-physical systems (CPSs), resilient machine learning for networked CPS, fog computing industrial CPS, etcElaborates classification of network abnormalities in Internet of Things-based cyber-physical systems (CPSs) using deep learningIncludes case studies and applications in the domain of smart grid systems, industrial control systems, smart manufacturing, social network and gaming, electric power grid and energy systems, etc