Overview

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

Full Product Details

Author:   K. Ananthajothi (Rajalakshmi Engineering College, Chennai, India) ,  S. N. Sangeethaa (Bannari Amman Institute of Technology, Tamil Nadu, India) ,  D. Divya (Jerusalem College of Engineering, Chennai, India) ,  S. Balamurugan (Albert Einstein Engineering and Research Labs, Tamil Nadu, India)
Publisher:   John Wiley & Sons Inc
Imprint:   Wiley-Scrivener
ISBN:  

9781394287734

ISBN 10:   1394287739
Pages:   400
Publication Date:   19 November 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock  
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Table of Contents

Preface xvii 1 Enhancing Safety and Security in Autonomous Connected Vehicles: Fusion of Optimal Control With Multi-Armed Bandit Learning 1 K.T. Meena Abarna, A. Punitha and S. Sathiya 1.1 Background 2 1.1.1 Problem Statement 4 1.1.2 Motivation 4 1.2 Related Works 5 1.2.1 Contributions 7 1.2.2 Centralized CRN Scheduling 8 1.2.3 Multi-Armed Bandit (MAB) 9 1.2.4 Bandit Learning with Switching Costs 11 1.3 System Model 12 1.3.1 Resource Spectrum 12 1.3.2 CRs’ Spectrum Utilization Schemes 13 1.3.3 CBS Scheduling 13 1.3.4 PUs’ Activity 13 1.4 Outcomes 15 1.4.1 Scenario I: Fallen Traffic Signs 15 1.4.2 Scenario II: Traffic Signs Alert by the Road Workers 16 1.4.3 Scenario III: Back/Rotated Traffic Sign Across the Road 17 1.4.4 Scenario IV: Hacking of a Stop Sign at a Four-Way Stop Intersection 18 1.5 Conclusions and Future Enhancement 19 1.5.1 Conclusions 19 1.5.2 Future Directions 21 References 23 2 Secure Data Handling in AI and Proactive Response Network: Create a Physical Layer–Proposed Cognitive Cyber-Physical Security 25 A. Sivasundari, P. Kumar, S. Vinodhkumar and N. Duraimurugan 2.1 Introduction 26 2.1.1 The Role of AI in Cybersecurity 27 2.1.2 Usage of CCPS in IoT 27 2.2 Challenges and Mechanisms 28 2.2.1 Brief Account of Challenges Faced 28 2.2.2 Innovative Mechanisms 30 2.3 Using AI to Support Cognitive Cybersecurity 30 2.3.1 Cognitive Systems 30 2.3.2 AI in IoT 30 2.4 Create a Physical Layer–Proposed CCPS 31 2.4.1 Create a Physical Layer–Proposed CCPS in Healthcare Application 33 2.4.1.1 Privacy-Aware Collaboration 33 2.4.1.2 Cycle Model of CCPS 36 2.4.1.3 Dynamic Security Knowledge Base 36 2.4.2 Method for Secure Data Handling 36 2.5 Road Map of Implementation 38 2.5.1 AI for CCPS-IoT 38 2.5.2 AI-Enabled Wireless CCPS-IoT to Provide Security 39 2.6 Conclusions and Future Enhancement 40 Future Directions 41 References 43 3 Intelligent Cognitive Cyber-Physical System–Based Intrusion Detection for AI-Enabled Security in Industry 4.0 45 V. Mahavaishnavi, R. Saminathan and G. Ramachandran 3.1 Introduction 46 3.1.1 Cyber-Physical Systems 46 3.1.2 Intelligent Cyber-Physical Systems (ISPS) 47 3.1.3 Cognitive Cyber-Physical Systems (CCPS) 48 3.1.4 IDS in Industry 4.0 Using iCCPS 49 3.1.5 AI in iCCPS-IDS 49 3.2 Problem Statement 50 3.3 Motivation 51 3.4 Research Gap 52 3.5 Methodology 53 3.5.1 Training Dataset 54 3.5.2 Information for Assessment and Instruction 54 3.5.3 Model 54 3.5.4 CPS Determined by Cognition Agents 56 3.5.5 Useful Implementation of the Actual Device 57 3.6 Importance and Impact of AI-Based Intrusion Detection in iCCPS in Industry 4.0 59 3.6.1 Need 59 3.6.2 Challenges 60 3.7 Conclusions and Future Directions 60 Future Directions 61 References 63 4 Resilient Cognitive Cyber-Physical Systems: Conceptual Frameworks, Models, and Implementation Strategies 65 R. Manivannan and M.P. Vaishnnave 4.1 Introduction 66 4.1.1 Problem Statement 70 4.1.2 Motivation 71 4.2 Materials and Methods 72 4.3 CCPS Design Challenges 74 4.4 Cyber-Physical Systems Principles and Paradigms 77 4.4.1 CCPS Conceptual Framework 79 4.4.2 CCPS Modeling 81 4.4.3 Other Modeling Issues in CCPS 82 4.5 Conclusions and Future Enhancements 83 4.5.1 Future Enhancements 83 References 85 5 Cognitive Cyber-Physical Security Challenges, Issues, and Recent Trends Over IoT 87 Chinnaraj Govindasamy 5.1 Introduction 88 5.1.1 From IoT to CCPS-IoT 93 5.1.2 Fundamental Cognitive Tasks 94 5.2 Motivation and Challenges 94 5.2.1 Motivation 94 5.2.2 Challenges 95 5.3 Security 96 5.3.1 Physical Layer Attacks 98 5.3.2 Physical Layer Security 99 5.3.3 Main Constituents 100 5.4 Research Gap 102 5.5 An Automatic Security Manager for CCPS Using IoT 103 5.5.1 Combatting Erroneous Estimations 103 5.5.2 Detection and Classification 104 5.6 Conclusions and Future Enhancement 104 Future Enhancement 105 References 106 6 Cognitive Cyber-Physical Security With IoT: A Solution to Smart Healthcare System 109 P. Shanmugam, Mohamed Iqbal M. and M. Amanullah 6.1 Introduction 110 6.1.1 Motivation 112 6.1.2 Need and Contribution 113 6.1.2.1 Need 113 6.1.2.2 Contribution 114 6.2 Medical CCPS with IoT 116 6.2.1 IoT Device for AI Solution 118 6.2.2 Traditional Bio-Modality Spoofing Detection 119 6.2.3 MCPS Using AI Device 119 6.3 Functional and Behavioral Perspectives 120 6.4 Modeling and Verification Methods of MCPS 123 6.4.1 MCPS Modeling Based on ICE 124 6.4.2 MCPS Modeling Based on Component 125 6.5 Artificial Intelligence for Cognitive Cybersecurity 125 6.5.1 Privacy-Aware Collaboration 127 6.5.2 Cognitive Security Cycle Model 127 6.6 Conclusions and Future Direction 128 6.6.1 Conclusions 128 6.6.2 Future Directions 129 References 130 7 Cognitive Cyber-Physical Security with IoT and ML: Role of Cybersecurity, Threats, and Benefits to Modern Economies and Industries 133 P. Anbalagan, A. Kanthimathinathan and S. Saravanan 7.1 Introduction 134 7.1.1 Key Contributions 136 7.1.2 Problem Statement 137 7.1.3 Motivation 138 7.2 CCPS Associated with IoT 139 7.2.1 Reasons in Favor of Cognitive Analytics 140 7.2.2 Analyses of Current Cyber Risk Data 141 7.3 Materials and Methods 143 7.3.1 Role of Cybersecurity in CCPS with IoT and ml 143 7.3.2 ml in Cognitive Cyber-Physical Security with IoT 144 7.3.3 Threats to Modern Economies and Industries 144 7.3.4 Benefits to Modern Economies and Industries 147 7.4 Outcomes 148 7.4.1 AI-Enabled Management Technology and Approach Taxonomy 151 7.4.2 Essential Self-Adapting System Technologies 151 7.4.3 Attack Malware Classifier 151 7.5 Conclusions and Future Direction 152 Future Directions 152 References 154 8 A Safety Analysis Framework for Medical Cyber-Physical Systems Using Systems Theory 157 K. Ananthajothi, K. Balamurugan, D. Divya and T.P. Latchoumi 8.1 Introduction 158 8.2 Background 160 8.2.1 Cyber-Physical Systems 160 8.2.2 Quality-of-Service Issues in CPS 161 8.2.3 Medical Cyber-Physical Systems 161 8.3 The Systems-Based Safety Analysis Observation for MCPS 162 8.3.1 Identification of Critical Requirements in MCPS 162 8.3.2 A Systems Theory–Based Method for Safety Analysis in Medical Cyber-Physical Systems 163 8.3.3 MCPS in Patient-Controlled Analgesia 165 8.4 Improved Wireless Medical Cyber-Physical System (IWMCPS) 166 8.4.1 Level: Data Acquisition 166 8.4.2 Layer: Data Aggregating 167 8.4.3 Level: Storing 167 8.4.4 Level: Action 168 8.4.5 IWMCPS Architectural Research 168 8.4.6 Core of Communications and Sensors 168 8.5 Hazard Analysis on PCA-MCPS 169 8.5.1 System Safety Constraint 170 8.5.2 System Safety Control Structure 170 8.5.3 Identify Unsafe Control Actions 170 8.5.4 Specifying Causes 171 8.6 Conclusions and Future Directions 172 Future Directions 172 References 174 9 Cognitive Cybersecurity and Reinforcement Learning: Enhancing Security in CPS-IoT Enabled Healthcare 177 A. Arokiaraj Jovith, M. Sangeetha, D. Saveetha and S. Antelin Vijila 9.1 Introduction 178 9.2 Methodology 182 9.2.1 Device AI Solutions 182 9.2.2 Detect the Spoofing of Bio-Modality 182 9.2.3 Detect the Spoofing of Bio-Modality Using Machine Learning 183 9.3 Challenges and Mechanisms 183 9.3.1 Challenges 183 9.3.2 Innovative Mechanisms 185 9.4 Cognitive Cyber-Physical Systems and Reinforcement Learning 185 9.4.1 Model Formulation 188 9.4.2 AI in CCPS 189 9.4.2.1 Privacy-Aware Collaboration 192 9.4.2.2 Cognitive Security Cycle Model 192 9.4.2.3 Need 193 9.4.2.4 Cross-Sectoral Techniques 193 9.4.2.5 Actuation and Data Collection 194 9.5 Conclusions and Future Directions 194 9.6 Future Directions 195 References 196 10 Navigating the Digital Landscape: Understanding, Detecting, and Mitigating Cyber Threats in an Evolving Technological Era 199 Manikandan J., Hemalatha P., Jayashree K. and Rajeswari P. 10.1 The Digital Transformation: Shaping Modern Business Dynamics 200 10.2 Impact of COVID-19: Accelerating the Digital Shift 201 10.3 Online Safety Concerns: Navigating the Digital Landscape 202 10.4 Interplay of Digital Technologies: Vulnerabilities and Threats 204 10.4.1 Introduction to Digital Technologies 204 10.4.2 Case Studies and Examples 206 10.5 Rise of Cyber Assaults as a Service: Automating Criminal Activities 207 10.6 Evolving Threat Landscape: Understanding Modern Cyber Attacks 210 10.7 Beyond Conventional Security Measures: The Need for Advanced Defense 211 10.8 Rise of Cyber Assaults as a Service: Automating Criminal Activities 213 10.8.1 Introduction to Cyber Assaults as a Service 213 10.8.2 Automation of Criminal Activities 213 10.8.3 Impact and Implications 214 10.9 Evolving Threat Landscape: Understanding Modern Cyber Attacks 215 10.9.1 Types of Modern Cyber Attacks 215 10.9.2 Implications for Cybersecurity Defense 216 10.10 Beyond Conventional Security Measures: The Need for Advanced Defense 217 10.10.1 Challenges with Conventional Security Measures 217 10.10.2 The Evolution of Advanced Defense 218 10.11 Uncovering Cyber Threats: Patterns, Trends, and Detection Methods 218 10.11.1 Patterns of Cyber Threats 218 10.12 Addressing Advanced Persistent Threats: Challenges and Solutions 220 10.12.1 Introduction to Advanced Persistent Threats (APTs) 220 10.12.2 Challenges Posed by APTs 220 10.12.3 Solutions for Addressing APTs 221 References 222 11 Defense Strategies for Cyber-Physical Systems 225 Rajendran Thanikachalam, T. Nithya, Balaji Sampathkumar and J. Mangayarkarasi 11.1 Introduction 226 11.2 Threat Landscape in CPS 228 11.3 Advanced Defense Strategies 231 11.3.1 Anomaly Detection in CPS 231 11.3.2 Secure Communication Protocols 232 11.3.3 Machine Learning-Driven Defenses 235 11.3.4 Zero Trust Model for CPS 237 11.3.5 Resilience Techniques for CPS 240 11.3.6 Intensive Training and Awareness 241 11.3.7 Conclusion and Future Directions 245 References 245 12 Cybersecurity in the Era of Artificial Intelligence: Challenges and Innovations 249 Ashwini A., H. Sehina and Banu Priya Prathaban 12.1 Introduction to Cybersecurity Analysis 250 12.2 Need for AI in Cybersecurity 252 12.3 Current Cybersecurity Techniques 253 12.4 Role of AI in Cybersecurity 255 12.5 Challenges in AI Enhanced Cybersecurity 256 12.6 Quantum Computing and Post Quantum Computing in Cybersecurity 257 12.7 AI Powered Encryption Analysis 259 12.8 Adaptive Cybersecurity 261 12.9 Overall Analysis of AI in Cybersecurity 262 12.10 Privacy Preserving AI and Cybersecurity 263 12.11 Future Directions and Research Challenges 264 12.12 Conclusion 266 References 266 13 Safeguarding the Virtual Realm: Assessing Cyber Security Challenges and Innovations in Today’s World 269 Rajaram P., Rajasekar Rangasamy, R. C. Karpagalakshmi, J. Lenin and S. Muthulingam 13.1 Introduction 270 13.2 Understanding the Motivations Behind Cyber Attacks: Financial, Political, and Military Goals 272 13.3 Types of Cyber Threats: From Viruses to Data Breaches 276 13.4 Impact of Cyber Attacks on Businesses and Governments: Financial and Operational Consequences 278 13.5 Strategies for Cyber Security: Prevention, Detection, and Response 281 13.6 Evolving Threat Landscape: Keeping Pace with Emerging Cyber Threats 283 13.7 Exploring Global Cyber Security Initiatives: Collaborative Efforts and Best Practices 285 13.8 Cyber Security Frameworks: Origins, Evolution, and Effectiveness 286 13.9 Emerging Trends in Cyber Security: AI, Blockchain, and IoT Solutions 288 13.10 Challenges and Limitations of Current Cyber Security Approaches 289 13.11 Future Directions in Cyber Security Research and Development 291 13.12 Conclusion 293 References 293 14 Predicting Android Ransomware Attacks Using Categorical Classification 295 A. Pandiaraj, N. Ramshankar, Mathan Kumar Mounagurusamy, Karakanapati Mrudhula, P. Lahari Sai and Lekkala Likhitha 14.1 Introduction 296 14.2 Background Study 297 14.3 Scope 300 14.4 Experimentation 300 14.5 Methodology 303 14.6 Conclusion 306 References 306 15 Defense Strategies for Cognitive Cyber-Physical Systems in Machine Learning Domain 309 M. Karthiga, N. Sangavi, V. R. Kiruthika, S. N. Sangeethaa, P. Ananthi and S. Vaanathi 15.1 Introduction 310 15.1.1 Background and Motivation 313 15.1.2 Challenges in CPS Defense 314 15.1.2.1 Resource Constraints and Real-Time Demands: Security in a Tight Spot 314 15.1.2.2 Data Security and Privacy: Balancing Protection with User Rights 314 15.1.2.3 Human Factors and Insider Threats: The Weakest Link 315 15.1.2.4 Evolving Threats: A Never-Ending Battle 315 15.2 Literature Review 315 15.3 CPS Security Fears 318 15.3.1 Vulnerabilities Posed in CPS 319 15.4 Secure Approaches for CPS: In Terms of Technology and Attack Perspectives 320 15.4.1 Security Strategies for Various Aspects of Attacks 320 15.5 Issues and Concerns for Ml Protection for CPS 322 15.5.1 ml Model Attacks and the Relevant Measures for Prevention 323 15.5.1.1 Dataset Poisoning Attacks 325 15.5.1.2 Black-Box Attack 327 15.5.1.3 White Box Attack 328 15.5.1.4 Backdoor Attacks 328 15.6 Countermeasures Against Dataset Poisoning Attempts 328 15.6.1 Simulated Poisoning Incidents 329 15.6.2 Countermeasures Against Model Poisoning Incidents 330 15.7 Vulnerability to Privacy 330 15.7.1 Process of Reverse Engineering and API Calls Disclosing Sensitive Data 331 15.8 Membership Inference Assaults 333 15.9 Runtime Disruption Assault 335 15.10 Comparative Investigation 336 15.11 Conclusion and Future Research Directions 338 References 339 16 Cyber-Physical Systems: Challenges, Opportunities, Security Solutions 343 Gopinathan S., S. Babu and P. Shanmugam 16.1 Cyber-Physical Systems 344 16.1.1 Introduction 344 16.1.2 Present Issues on Cyber Security 345 16.1.2.1 Phishing Exploits 346 16.1.2.2 Internet of Things Ransomware 347 16.1.2.3 Strengthened Regulation of Data Privacy 347 16.1.2.4 Cyberattacks Using Mobile Technology 347 16.1.2.5 A Higher Allocation of Resources to Automation 347 16.1.3 CPS –Applications and Research Areas 348 16.2 Cyber Security Challenges 351 16.2.1 Social Media Role in Cyber-Security 352 16.2.2 Cyber-Security Methods 352 16.2.2.1 Access Management and Passphrase Protection 352 16.2.2.2 Verification of Data 352 16.2.2.3 Malicious Software Detectors 353 16.2.2.4 Network Security Barriers 353 16.2.2.5 Antimalware 353 16.3 Integration of Physical and Digital 353 16.3.1 Materials and Procedures 354 16.3.2 Applications 355 16.3.2.1 Financial Sector 355 16.3.2.2 Health Division 355 16.3.2.3 Business Sector 356 16.3.2.4 Industry Sector 356 16.4 Digital Threats to Physical Systems 357 16.4.1 Threats Prioritization 357 16.4.2 Selection of Security Requirements 358 16.5 Industry 4.0 Security 359 16.5.1 Classification of Cyber-Physical Systems and their Pertinent Themes within the Framework of Industry 4.0 360 16.5.2 The Digital Supply System 361 16.5.2.1 The Data Sharing Hazards Associated with the Digital Supply System 361 16.5.2.2 Data Sharing: Granted Access to Information for More Parties 362 16.5.3 Cybersecurity Challenges in Industry 4.0 363 16.6 Evaluation of Risk for CPS 364 16.6.1 Safety Risk Assessment Standards 364 16.6.2 Approaches for Safety Risk Evaluation in CPS 365 16.6.2.1 Analysis of Fault Trees 365 16.6.2.2 Failure Modes and Impacts Evaluation (fmie) 365 16.6.2.3 The Menace and Operability Approach 365 16.6.2.4 Model-Centred Engineering 366 16.6.2.5 Master Logic Illustration with Objective Tree - Accomplishment Tree 366 16.6.2.6 System Theoretical Accident Model and Procedures (STAMP) is the Foundation for System Theoretic Process Analysis, a Hazard Analysis Method 366 References 366 Index 369

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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. Sheng-Lung Peng, PhD is a Professor and the Director of the Department of Creative Technologies and Product Design at the National Taipei University of Business, Taiwan. He has published more than 100 research papers in addition to his role as a visiting professor and board member for several international universities and academic groups. His research interests include designing and analyzing algorithms for bioinformatics, combinatorics, data mining, and networks.

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