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Securing Cyber-Physical Systems

Fundamentals, Applications, and Challenges

Edited by K. Ananthajothi, S. N. Sangeethaa, D. Divya, S. Balamurugan and Shen-Lung Peng
Series: Industry 5.0 Transformation Applications
Copyright: 2025   |   Expected Pub Date:2025/09/30
ISBN: 9781394287734  |  Hardcover  |  
396 pages

One Line Description
Protect critical infrastructure from emerging threats with this essential guide, providing an in-depth exploration of innovative defense strategies and practical solutions for securing cyber-physical systems.

Audience
Researchers, cybersecurity professionals, information technologists and industry leaders innovating infrastructure to protect against digital threats.

Description
As industries increasingly rely on the convergence of digital and physical infrastructures, the need for robust cybersecurity solutions has grown. This book addresses the key challenges posed by integrating digital technologies into critical physical systems across various sectors, including energy, healthcare, and manufacturing. Focusing on innovative defence strategies and practical solutions, this book provides an in-depth exploration of the vulnerabilities and defence mechanisms essential to securing cyber-physical systems. The book is designed to equip researchers, cybersecurity professionals, and industry leaders with the knowledge to protect critical infrastructure from emerging digital threats. From understanding complex vulnerabilities to implementing secure system designs, this volume offers a comprehensive guide to fortifying and securing the systems that shape our modern, interconnected world.
Readers will find the volume:
• Explores the evolving threat landscape, encompassing potential attacks on critical infrastructure, industrial systems, and interconnected devices;
• Examines vulnerabilities inherent in cyber-physical systems, such as weak access controls, insecure communication channels, and the susceptibility of physical components to digital manipulation;
• Uses real-world case studies to introduce strategies for assessing and quantifying the cybersecurity risks associated with cyber-physical systems, considering the potential consequences of system breaches;
• Provides an overview of cybersecurity measures and defense mechanisms designed to fortify cyber-physical systems against digital threats, including intrusion detection systems, encryption, and security best practices;
• Discusses existing and emerging regulatory frameworks aimed at enhancing cybersecurity in critical infrastructure and physical systems.

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Author / Editor Details
K. Ananthajothi, PhD is a Professor in the Department of Computer Science and Engineering at Rajalakshmi Engineering College, Chennai, India. He has published one book, two patents, and several research papers in international journals and conferences. His research focuses on machine learning and deep learning.

S. N. Sangeethaa, PhD is a Professor in the Department of Computer Science and Engineering at the Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu, India. She has published seven books, more than 25 research articles in reputable journals, and more than 50 papers in national and international conferences. Her research interests include artificial intelligence, machine learning, and image processing.

D. Divya, PhD is an Assistant Professor in the Department of Computer Science and Engineering at Misrimal Navajee Munoth Jain Engineering College, Chennai, India. She has published several papers in international journals. Her research focuses on data mining and machine learning.

S. Balamurugan, PhD is the Director of Albert Einstein Engineering and Research Labs and the Vice-Chairman of the Renewable Energy Society of India. He has published more than 60 books, 300 articles in national and international journals and conferences, and 200 patents. His research interests include artificial intelligence, augmented reality, Internet of Things, big data analytics, cloud computing, and wearable computing.

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Table of Contents
Preface
1. Enhancing Safety and Security in Autonomous Connected Vehicles: Fusion of Optimal Control With Multi-Armed Bandit Learning
K.T. Meena Abarna, A. Punitha and S. Sathiya
1.1 Background
1.1.1 Problem Statement
1.1.2 Motivation
1.2 Related Works
1.2.1 Contributions
1.2.2 Centralized CRN Scheduling
1.2.3 Multi-Armed Bandit (MAB)
1.2.4 Bandit Learning with Switching Costs
1.3 System Model
1.3.1 Resource Spectrum
1.3.2 CRs’ Spectrum Utilization Schemes
1.3.3 CBS Scheduling
1.3.4 PUs’ Activity
1.4 Outcomes
1.4.1 Scenario I: Fallen Traffic Signs
1.4.2 Scenario II: Traffic Signs Alert by the Road Workers
1.4.3 Scenario III: Back/Rotated Traffic Sign Across the Road
1.4.4 Scenario IV: Hacking of a Stop Sign at a Four-Way Stop Intersection
1.5 Conclusions and Future Enhancement
1.5.1 Conclusions
1.5.2 Future Directions
References
2. Secure Data Handling in AI and Proactive Response Network: Create a Physical Layer–Proposed Cognitive Cyber-Physical Security
A. Sivasundari, P. Kumar, S. Vinodhkumar and N. Duraimurugan
2.1 Introduction
2.1.1 The Role of AI in Cybersecurity
2.1.2 Usage of CCPS in IoT
2.2 Challenges and Mechanisms
2.2.1 Brief Account of Challenges Faced
2.2.2 Innovative Mechanisms
2.3 Using AI to Support Cognitive Cybersecurity
2.3.1 Cognitive Systems
2.3.2 AI in IoT
2.4 Create a Physical Layer–Proposed CCPS
2.4.1 Create a Physical Layer–Proposed CCPS in Healthcare Application
2.4.1.1 Privacy-Aware Collaboration
2.4.1.2 Cycle Model of CCPS
2.4.1.3 Dynamic Security Knowledge Base
2.4.2 Method for Secure Data Handling
2.5 Road Map of Implementation
2.5.1 AI for CCPS-IoT
2.5.2 AI-Enabled Wireless CCPS-IoT to Provide Security
2.6 Conclusions and Future Enhancement
Future Directions
References
3. Intelligent Cognitive Cyber-Physical System–Based Intrusion Detection for AI-Enabled Security in Industry 4.0
V. Mahavaishnavi, R. Saminathan and G. Ramachandran
3.1 Introduction
3.1.1 Cyber-Physical Systems
3.1.2 Intelligent Cyber-Physical Systems (ISPS)
3.1.3 Cognitive Cyber-Physical Systems (CCPS)
3.1.4 IDS in Industry 4.0 Using iCCPS
3.1.5 AI in iCCPS-IDS
3.2 Problem Statement
3.3 Motivation
3.4 Research Gap
3.5 Methodology
3.5.1 Training Dataset
3.5.2 Information for Assessment and Instruction
3.5.3 Model
3.5.4 CPS Determined by Cognition Agents
3.5.5 Useful Implementation of the Actual Device
3.6 Importance and Impact of AI-Based Intrusion Detection in iCCPS in Industry 4.0
3.6.1 Need
3.6.2 Challenges
3.7 Conclusions and Future Directions
Future Directions
References
4. Resilient Cognitive Cyber-Physical Systems: Conceptual Frameworks, Models, and Implementation Strategies
R. Manivannan and M.P. Vaishnnave
4.1 Introduction
4.1.1 Problem Statement
4.1.2 Motivation
4.2 Materials and Methods
4.3 CCPS Design Challenges
4.4 Cyber-Physical Systems Principles and Paradigms
4.4.1 CCPS Conceptual Framework
4.4.2 CCPS Modeling
4.4.3 Other Modeling Issues in CCPS
4.5 Conclusions and Future Enhancements
4.5.1 Future Enhancements
References
5. Cognitive Cyber-Physical Security Challenges, Issues, and Recent Trends Over IoT
Chinnaraj Govindasamy
5.1 Introduction
5.1.1 From IoT to CCPS-IoT
5.1.2 Fundamental Cognitive Tasks
5.2 Motivation and Challenges
5.2.1 Motivation
5.2.2 Challenges
5.3 Security
5.3.1 Physical Layer Attacks
5.3.2 Physical Layer Security
5.3.3 Main Constituents
5.4 Research Gap
5.5 An Automatic Security Manager for CCPS Using IoT
5.5.1 Combatting Erroneous Estimations
5.5.2 Detection and Classification
5.6 Conclusions and Future Enhancement
Future Enhancement
References
6. Cognitive Cyber-Physical Security With IoT: A Solution to Smart Healthcare System
P. Shanmugam, Mohamed Iqbal M. and M. Amanullah
6.1 Introduction
6.1.1 Motivation
6.1.2 Need and Contribution
6.1.2.1 Need
6.1.2.2 Contribution
6.2 Medical CCPS with IoT
6.2.1 IoT Device for AI Solution
6.2.2 Traditional Bio-Modality Spoofing Detection
6.2.3 MCPS Using AI Device
6.3 Functional and Behavioral Perspectives
6.4 Modeling and Verification Methods of MCPS
6.4.1 MCPS Modeling Based on ICE
6.4.2 MCPS Modeling Based on Component
6.5 Artificial Intelligence for Cognitive Cybersecurity
6.5.1 Privacy-Aware Collaboration
6.5.2 Cognitive Security Cycle Model
6.6 Conclusions and Future Direction
6.6.1 Conclusions
6.6.2 Future Directions
References
7. Cognitive Cyber-Physical Security with IoT and ML: Role of Cybersecurity, Threats, and Benefits to Modern Economies and Industries
P. Anbalagan, A. Kanthimathinathan and S. Saravanan
7.1 Introduction
7.1.1 Key Contributions
7.1.2 Problem Statement
7.1.3 Motivation
7.2 CCPS Associated with IoT
7.2.1 Reasons in Favor of Cognitive Analytics
7.2.2 Analyses of Current Cyber Risk Data
7.3 Materials and Methods
7.3.1 Role of Cybersecurity in CCPS with IoT and ML
7.3.2 ML in Cognitive Cyber-Physical Security with IoT
7.3.3 Threats to Modern Economies and Industries
7.3.4 Benefits to Modern Economies and Industries
7.4 Outcomes
7.4.1 AI-Enabled Management Technology and Approach Taxonomy
7.4.2 Essential Self-Adapting System Technologies
7.4.3 Attack Malware Classifier
7.5 Conclusions and Future Direction
Future Directions
References
8. A Safety Analysis Framework for Medical Cyber-Physical Systems Using Systems Theory
K. Ananthajothi, K. Balamurugan, D. Divya and T.P. Latchoumi
8.1 Introduction
8.2 Background
8.2.1 Cyber-Physical Systems
8.2.2 Quality-of-Service Issues in CPS
8.2.3 Medical Cyber-Physical Systems
8.3 The Systems-Based Safety Analysis Observation for MCPS
8.3.1 Identification of Critical Requirements in MCPS
8.3.2 A Systems Theory–Based Method for Safety Analysis in Medical Cyber-Physical Systems
8.3.3 MCPS in Patient-Controlled Analgesia
8.4 Improved Wireless Medical Cyber-Physical System (IWMCPS)
8.4.1 Level: Data Acquisition
8.4.2 Layer: Data Aggregating
8.4.3 Level: Storing
8.4.4 Level: Action
8.4.5 IWMCPS Architectural Research
8.4.6 Core of Communications and Sensors
8.5 Hazard Analysis on PCA-MCPS
8.5.1 System Safety Constraint
8.5.2 System Safety Control Structure
8.5.3 Identify Unsafe Control Actions
8.5.4 Specifying Causes
8.6 Conclusions and Future Directions
Future Directions
References
9. Cognitive Cybersecurity and Reinforcement Learning: Enhancing Security in CPS-IoT Enabled Healthcare
A. Arokiaraj Jovith, M. Sangeetha, D. Saveetha and S. Antelin Vijila
9.1 Introduction
9.2 Methodology
9.2.1 Device AI Solutions
9.2.2 Detect the Spoofing of Bio-Modality
9.2.3 Detect the Spoofing of Bio-Modality Using Machine Learning
9.3 Challenges and Mechanisms
9.3.1 Challenges
9.3.2 Innovative Mechanisms
9.4 Cognitive Cyber-Physical Systems and Reinforcement Learning
9.4.1 Model Formulation
9.4.2 AI in CCPS
9.4.2.1 Privacy-Aware Collaboration
9.4.2.2 Cognitive Security Cycle Model
9.4.2.3 Need
9.4.2.4 Cross-Sectoral Techniques
9.4.2.5 Actuation and Data Collection
9.5 Conclusions and Future Directions
9.6 Future Directions
References
10. Navigating the Digital Landscape: Understanding, Detecting, and Mitigating Cyber Threats in an Evolving Technological Era
Manikandan J., Hemalatha P., Jayashree K. and Rajeswari P.
10.1 The Digital Transformation: Shaping Modern Business Dynamics
10.2 Impact of COVID-19: Accelerating the Digital Shift
10.3 Online Safety Concerns: Navigating the Digital Landscape
10.4 Interplay of Digital Technologies: Vulnerabilities and Threats
10.4.1 Introduction to Digital Technologies
10.4.2 Case Studies and Examples
10.5 Rise of Cyber Assaults as a Service: Automating Criminal Activities
10.6 Evolving Threat Landscape: Understanding Modern Cyber Attacks
10.7 Beyond Conventional Security Measures: The Need for Advanced Defense
10.8 Rise of Cyber Assaults as a Service: Automating Criminal Activities
10.8.1 Introduction to Cyber Assaults as a Service
10.8.2 Automation of Criminal Activities
10.8.3 Impact and Implications
10.9 Evolving Threat Landscape: Understanding Modern Cyber Attacks
10.9.1 Types of Modern Cyber Attacks
10.9.2 Implications for Cybersecurity Defense
10.10 Beyond Conventional Security Measures: The Need for Advanced Defense
10.10.1 Challenges with Conventional Security Measures
10.10.2 The Evolution of Advanced Defense
10.11 Uncovering Cyber Threats: Patterns, Trends, and Detection Methods
10.11.1 Patterns of Cyber Threats
10.12 Addressing Advanced Persistent Threats: Challenges and Solutions
10.12.1 Introduction to Advanced Persistent Threats (APTs)
10.12.2 Challenges Posed by APTs
10.12.3 Solutions for Addressing APTs
References
11. Defense Strategies for Cyber-Physical Systems
Rajendran Thanikachalam, T. Nithya, Balaji Sampathkumar and J. Mangayarkarasi
11.1 Introduction
11.2 Threat Landscape in CPS
11.3 Advanced Defense Strategies
11.3.1 Anomaly Detection in CPS
11.3.2 Secure Communication Protocols
11.3.3 Machine Learning-Driven Defenses
11.3.4 Zero Trust Model for CPS
11.3.5 Resilience Techniques for CPS
11.3.6 Intensive Training and Awareness
11.3.7 Conclusion and Future Directions
References
12. Cybersecurity in the Era of Artificial Intelligence: Challenges and Innovations
Ashwini A., H. Sehina and Banu Priya Prathaban
12.1 Introduction to Cybersecurity Analysis
12.2 Need for AI in Cybersecurity
12.3 Current Cybersecurity Techniques
12.4 Role of AI in Cybersecurity
12.5 Challenges in AI Enhanced Cybersecurity
12.6 Quantum Computing and Post Quantum Computing in Cybersecurity
12.7 AI Powered Encryption Analysis
12.8 Adaptive Cybersecurity
12.9 Overall Analysis of AI in Cybersecurity
12.10 Privacy Preserving AI and Cybersecurity
12.11 Future Directions and Research Challenges
12.12 Conclusion
References
13. Safeguarding the Virtual Realm: Assessing Cyber Security Challenges and Innovations in Today’s World
Rajaram P., Rajasekar Rangasamy, R. C. Karpagalakshmi, J. Lenin and S. Muthulingam
13.1 Introduction
13.2 Understanding the Motivations Behind Cyber Attacks: Financial, Political, and Military Goals
13.3 Types of Cyber Threats: From Viruses to Data Breaches
13.4 Impact of Cyber Attacks on Businesses and Governments: Financial and Operational Consequences
13.5 Strategies for Cyber Security: Prevention, Detection, and Response
13.6 Evolving Threat Landscape: Keeping Pace with Emerging Cyber Threats
13.7 Exploring Global Cyber Security Initiatives: Collaborative Efforts and Best Practices
13.8 Cyber Security Frameworks: Origins, Evolution, and Effectiveness
13.9 Emerging Trends in Cyber Security: AI, Blockchain, and IoT Solutions
13.10 Challenges and Limitations of Current Cyber Security Approaches
13.11 Future Directions in Cyber Security Research and Development
13.12 Conclusion
References
14. Predicting Android Ransomware Attacks Using Categorical Classification
A. Pandiaraj, N. Ramshankar, Mathan Kumar Mounagurusamy, Karakanapati Mrudhula, P. Lahari Sai and Lekkala Likhitha
14.1 Introduction
14.2 Background Study
14.3 Scope
14.4 Experimentation
14.5 Methodology
14.6 Conclusion
References
15. Defense Strategies for Cognitive Cyber-Physical Systems in Machine Learning Domain
M. Karthiga, N. Sangavi, V. R. Kiruthika, S. N. Sangeethaa, P. Ananthi and S. Vaanathi
15.1 Introduction
15.1.1 Background and Motivation
15.1.2 Challenges in CPS Defense
15.1.2.1 Resource Constraints and Real-Time Demands: Security in a Tight Spot
15.1.2.2 Data Security and Privacy: Balancing Protection with User Rights
15.1.2.3 Human Factors and Insider Threats: The Weakest Link
15.1.2.4 Evolving Threats: A Never-Ending Battle
15.2 Literature Review
15.3 CPS Security Fears
15.3.1 Vulnerabilities Posed in CPS
15.4 Secure Approaches for CPS: In Terms of Technology and Attack Perspectives
15.4.1 Security Strategies for Various Aspects of Attacks
15.5 Issues and Concerns for Ml Protection for CPS
15.5.1 ML Model Attacks and the Relevant Measures for Prevention
15.5.1.1 Dataset Poisoning Attacks
15.5.1.2 Black-Box Attack
15.5.1.3 White Box Attack
15.5.1.4 Backdoor Attacks
15.6 Countermeasures Against Dataset Poisoning Attempts
15.6.1 Simulated Poisoning Incidents
15.6.2 Countermeasures Against Model Poisoning Incidents
15.7 Vulnerability to Privacy
15.7.1 Process of Reverse Engineering and API Calls Disclosing Sensitive Data
15.8 Membership Inference Assaults
15.9 Runtime Disruption Assault
15.10 Comparative Investigation
15.11 Conclusion and Future Research Directions
References
16. Cyber-Physical Systems: Challenges, Opportunities, Security Solutions
Gopinathan S., S. Babu and P. Shanmugam
16.1 Cyber-Physical Systems
16.1.1 Introduction
16.1.2 Present Issues on Cyber Security
16.1.2.1 Phishing Exploits
16.1.2.2 Internet of Things Ransomware
16.1.2.3 Strengthened Regulation of Data Privacy
16.1.2.4 Cyberattacks Using Mobile Technology
16.1.2.5 A Higher Allocation of Resources to Automation
16.1.3 CPS –Applications and Research Areas
16.2 Cyber Security Challenges
16.2.1 Social Media Role in Cyber-Security
16.2.2 Cyber-Security Methods
16.2.2.1 Access Management and Passphrase Protection
16.2.2.2 Verification of Data
16.2.2.3 Malicious Software Detectors
16.2.2.4 Network Security Barriers
16.2.2.5 Antimalware
16.3 Integration of Physical and Digital
16.3.1 Materials and Procedures
16.3.2 Applications
16.3.2.1 Financial Sector
16.3.2.2 Health Division
16.3.2.3 Business Sector
16.3.2.4 Industry Sector
16.4 Digital Threats to Physical Systems
16.4.1 Threats Prioritization
16.4.2 Selection of Security Requirements
16.5 Industry 4.0 Security
16.5.1 Classification of Cyber-Physical Systems and their Pertinent Themes within the Framework of Industry 4.0
16.5.2 The Digital Supply System
16.5.2.1 The Data Sharing Hazards Associated with the Digital Supply System
16.5.2.2 Data Sharing: Granted Access to Information for More Parties
16.5.3 Cybersecurity Challenges in Industry 4.0
16.6 Evaluation of Risk for CPS
16.6.1 Safety Risk Assessment Standards
16.6.2 Approaches for Safety Risk Evaluation in CPS
16.6.2.1 Analysis of Fault Trees
16.6.2.2 Failure Modes and Impacts Evaluation (FMIE)
16.6.2.3 The Menace and Operability Approach
16.6.2.4 Model-Centred Engineering
16.6.2.5 Master Logic Illustration with Objective Tree - Accomplishment Tree
16.6.2.6 System Theoretical Accident Model and Procedures (STAMP) is the Foundation for System Theoretic Process Analysis, a Hazard Analysis Method
References
Index

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