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Full Description
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 management
Showcases cyber-physical systems (CPSs) security solutions, lightweight cryptographic solutions, and CPS forensics, etc
Emphasizes machine learning methods for behavior-based intrusion detection in cyber-physical systems (CPSs), resilient machine learning for networked CPS, fog computing industrial CPS, etc
Elaborates classification of network abnormalities in Internet of Things-based cyber-physical systems (CPSs) using deep learning
Includes 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
Contents
Section I Introduction to Cyber Physical System
1. Cyber-Physical Systems and Their Emergence in Machine Learning
Moushumi Das and Vandana Mohindru Sood
Section II Security Concepts in Cyber-Physical System
2. A General Walkthrough of the Cyber-Physical Systems Concerning
Security Threats and Safety Measures
Indranath Roy
3. Cyber-Physical System Security Attack Detection Methods and Models.
Gurleen Kaur, Kapil Mehta, and Saumya Rajvanshi
Section III Securing Cyber-Physical Systems
4. Lightweight Cryptographic Algorithms for Cyber-Physical Systems.
Sheikh Imroza Manzoor and Yashwant Singh
5. Lightweight Cryptographic Solutions for Resource-constrained Devices in Cyber-Physical System.
G Krishna Pranav, Zeesha Mishra, and Bibhudendra
6. Performance Analysis of Machine Learning Classifiers for Detection of Phishing Websites.
Asadullah Safi, Satwinder Singh, Gurpreet Kaur, Meenakshi, and Tripat Kaur
7. Cybersecurity Issues and Artificial Intelligence-Based Solutions in Cyber-Physical Systems.
Narinder Verma, Neerendra Kumar, Zakir Ahmad Sheikh, Neha Koul, and Ankit Ashish
Section IV Machine Learning for Cyber-Physical Systems
8. A Machine Learning-Based Smart Framework for Intrusion Detection in Cyber-Physical Systems.
Hitakshi, Vandana Mohindru Sood, Kapil Mehta, and Gurleen Kaur
9. Machine Learning Techniques for Real-Time Concept Drift Detection in Industrial Cyber-Physical Systems.
Sangeeta Arora and Sushil Kumar Narang
10. A Hybrid Machine Learning Approach for Intrusion Detection in Cyber-Physical Manufacturing Systems.
Jithish J, Sriram Sankaran, and Krishnashree Achuthan
11. Machine Learning-Based Early Diagnosis of Unstable Cyber-Physical Systems.
Saumya Rajvanshi, Gurleen Kaur, and Kapil Mehta
Section V Application Domains in Cyber-Physical Systems: Challenges, Trends, and Future Scope
12. Challenges Associated with Cybersecurity for Smart Grids Based on IoT.
Suprava Ranjan Laha, Binod Kumar Pattanayak, Saumendra Pattnaik, and
Mohammad Reza Hosenkhan
13. Cybersecurity Challenges in IoT-Based Healthcare Systems: A Survey.
Suprava Ranjan Laha and Debasish Swapnesh Kumar Nayak
14. Rapid Advancement and Trends of Big Data Analytics and Cyber-Physical System Embedded in Healthcare and Industry 4.0.
Chintan Singh, Himanshu Khajuria, and Biswa Prakash Nayak
15. Blockchain-Based Cyber-Physical System: Opportunities and Challenges.
Veerpal Kaur, Devershi Pallavi Bhatt, Sumegh Tharewal, and Pradeep Kumar Tiwari
16. Cybersecurity Challenges, Trends, and Future Directions for Smart Agriculture.
Aditya Sharma and Kamal Deep Garg
