Preface xxv

1 Cross-Border Healthcare Data Sharing Using Blockchain and Federated Learning 1
Bipin Kumar Rai, Chin-Shiuh Shieh and Anoop Kumar Srivastava

1.1 Introduction 2
1.2 Related Work 3
1.3 Role of Blockchain in Cross-Border Federated Learning in Healthcare 7
1.4 Major Research Trends 9
1.5 Common Datasets and Benchmarks 10
1.6 Prevailing Challenges and Open Research Gaps 10
1.7 Promising Directions for Future Work 13
1.8 Practical Notes for Deployment 13
1.9 Conclusion 14

2 The Role of Artificial Intelligence in Privacy-Aware Data Collaboration 17
Kumar Dilip, Bipin Kumar Rai and Yashwant Shukla

2.1 Introduction 18
2.2 Background and Primitives 18
2.3 Taxonomy of Privacy-Aware Collaborative AI 22
2.4 Mathematical Formulation: Privacy–Utility–Efficiency Trade-Off 25
2.5 System Design Patterns and Examples 28
2.6 Privacy-Preserving Explainable AI 29
2.7 Legal, Ethical, and Governance Consideration 31
2.8 Performance, Efficiency, and System Engineering 33
2.9 Evaluation Metrics and Benchmarks 36
2.10 Open Problem and Research Agenda 39
2.11 Conclusion 42

3 Understanding Data Privacy in the Age of Distributed AI 47
Ayush Tripathi, Prashant Upadhyay, Pawan Kumar and Sinem Alturjman

3.1 Introduction 48Contents vii
3.2 Distributed Intelligence and the Shift toward PrivacyPreserving AI 50
3.3 The Privacy Problems in the Contemporary Distributed AI World 53
3.4 Generalized Privacy-Preserving Techniques That Support Secure Distributed AI 55
3.5 Distributed Artificial Intelligence Blockchain Foundations of Trust and Transparency 58
3.6 Edge and Fog Computing As the Strengths of Distributed AI 60
3.7 Regulatory Landscapes and Ethical Expectations in Distributed Artificial Intelligence 62
3.8 Future Scope 66
3.9 Conclusion 67

4 Blockchain Technology for Secure and Ethical AI-Driven Healthcare 71
Jaishree Jain, Updesh Kumar Jaiswal, Shraddha Mishra and Mani Dublish

4.1 Introduction 72
4.2 Literature Review 74
4.3 Artificial Intelligence Possible Attacks 77
4.4 Blockchain-Based AI Healthcare Solution 80
4.5 Blockchain-Based AI Healthcare Methods Results 87
4.6 Conclusion 90

5 Federated Learning and Blockchain: A Collaborative Paradigm for Secure and Decentralized AI 95
Sonam Gupta and Pradeep Gupta

5.1 Introduction 96
5.2 Fundamental Principles and Architecture 96
5.3 Privacy and Security Mechanisms 99
5.4 Algorithmic Foundations 100
5.5 Blockchain Integration in Federated Learning 101
5.6 Applications and Use Cases 103
5.7 Technical Challenges and Solutions 104
5.8 Evaluation Metrics and Benchmarks 106
5.9 Future Directions and Emerging Trends 108
5.10 Conclusion 109

6 Smart Contracts-Based Autonomous Governance System for Smart City 113
Pawan Kumar, Rupa Rani, Jyoti Rani, Santosh Kumar Mishra and Shivpratap Singh Kushwah

6.1 Introduction 114
6.2 Smart City 116
6.3 Challenges in Smart City 117
6.4 Smart Contracts 119
6.5 Smart Contracts in Smart City 124

7 Securing Legal Practice in Nigeria: Integrating AI and Blockchain for Cyber Resilience 133
Udebuani, Chidiogo Mercy and Rajesh Prasad

7.1 Introduction 134
7.2 The Role of AI and Blockchain in Enhancing Legal Practice and Cybersecurity 138
7.3 Strategic Pathways for Nigeria's Legal Sector 139
7.4 Nigerian Legal-Regulatory and Evidentiary Context 139
7.5 AI for Cyber-Resilient Legal Practice 141
7.6 Blockchain for Integrity, Auditability, and Trust 142
7.7 AI–Blockchain Integration: A Reference Architecture for Law Firms 142
7.8 Implementation Roadmap for Nigerian Law Firms 147
7.9 Conclusion and Recommendations 150
7.10 Conclusion 156

8 Encouraging Secure Collaboration: AI's Function in Privacy-Aware Data Governance and Sharing 161
Mani Dublish, Updesh Kumar Jaiswal, Jaishree Jain and Shikha Mittal

8.1 Introduction 162
8.2 Background and Literature Review 165
8.3 Foundations of Privacy-Aware Data Governance 167
8.4 AI Techniques for Privacy-Aware Data Sharing 169
8.5 Secure Data Collaboration Architectures Powered by AI 172
8.6 Cross-Sector Use Cases 175
8.7 Risks, Challenges, and Limitations 179
8.8 Compliance and Regulatory Alignment 181
8.9 Future Trends and Research Directions 183
8.10 Conclusion 186

9 Criminal Identification System Using Face Detection with Artificial Intelligence 193
Sunil Gupta, Tejas Singhal, Aman Kumar, Bipin Kumar Rai and Kamal Saluja

9.1 Introduction 194
9.2 Related Work 196
9.3 Objectives and Scope 197
9.4 Methodology 199
9.5 Results and Discussion 201Contents xiii
9.6 Conclusion 207

10 Zero-Knowledge Proofs for Model Integrity and Privacy 211
A. Kishore Kumar, T. Nivethitha, P.K. Poonguzhali and D. Saranyanandhini

10.1 Introduction 212
10.2 Decentralized Collaborative Learning: Security and Privacy Challenges 219
10.3 Introduction of ZKPs to Frameworks of Collaborative Learning 226
10.4 ZKPs for Model Provenance and Integrity Verification 230
10.5 Protection and Implementation Frameworks and Tools 236
10.6 Use Cases and Case Studies 241
10.7 Conclusion and Future Directions 245

11 Edge and Fog Computing for Distributed Intelligence 251
Vadym Slyusar

11.1 Introduction 252
11.2 Differences Between Fog Computing and the Distribution of a Multi-Agent System Across Multiple Edge Devices 254
11.3 Combined Architecture Integrating Fog Computing and Multi-Agent Distribution at the Edge 256
11.4 Cognitive Decentralized Systems 257
11.5 Concept of Loitering Models 260
11.6 Migration Protocol with Decision-Making Metrics 263
11.7 Splitting of Models 267
11.8 Swarms of Loitering Models 272
11.9 Architecture with Distributed Embedding 275
11.10 The Concept of the Embedding Swarm 278
11.11 Hardware Aspects of the Edge Level 280
11.12 Conclusion 282

12 Incentive Models and Token Economics in Learning Networks 287
Raj Kishor Verma, Atul Kumar Rai, Kumar Dilip and Shivani Sharma

12.1 Introduction 288
12.2 Background 290
12.3 Smart Contract Mechanisms 293
12.4 Literature Review 303
12.5 Proposed Methodology 303
12.6 Conclusion and Future Scope 317
12.7 Challenges 319

13 Healthcare Applications of Blockchain–AI Collaboration 323
Rishabh Kamal and Prashant Upadhyay

13.1 Introduction 324
13.2 Literature Review 329
13.3 Fundamentals of Blockchain and Artificial Intelligence 332
13.4 Applications of Blockchain and Artificial Intelligence in Healthcare 334
13.5 Challenges in Integrating Blockchain and AI in Healthcare 338
13.6 Future Directions in Healthcare Technology 340
13.7 Conclusion 343

14 Financial Sector Use Cases—Privacy-Preserving Fraud Detection 349
Ayush Tripathi, Prashant Upadhyay, Rupa Rani and Chadi Altrjman

14.1 Introduction 350
14.2 Traditional vs. Decentralized Fraud Detection Systems 353
14.3 Federated Learning for Collaborative Fraud Detection 357
14.4 Privacy-Hyphenated Systems of Financial Fraud Detection 360
14.5 Blockchain and Smart Contracts for Trustworthy Fraud Intelligence 363
14.6 Regulatory and Ethical Aspects of Privacy 369
14.7 Future Scope 372
14.8 Conclusion 373

15 Smart Cities through IoT, Blockchain, and AI Collaboration 377
Vishal Jain, Sachin Jain and K. Ramkumar

15.1 Introduction 378
15.2 Literature Review 381
15.3 The Collaborative Framework: Integrating IoT, Blockchain, and AI 383
15.4 Mathematical and Algorithmic Foundations 387
15.5 Graphical Representations of the Ecosystem 392
15.6 Case Studies: Practical Applications and Implementations 395
15.7 Challenges and Future Research Directions 397
15.8 Conclusion 398

16 Legal and Regulatory Challenges of Cross-Border AI Collaboration 403
Sachin Jain, Vishal Jain, Danish Ather, Golnoosh Manteghi and Abu Bakar Abdul Hamid

16.1 Introduction 404
16.2 Literature Review: Mapping the Legal Minefield 406
16.3 Conceptual Models: Quantifying and Visualizing Legal Complexity 409
16.4 Descriptive Visualizations of the Legal Ecosystem 413
16.5 Case Studies: The Law in Action 415
16.6 Overarching Challenges and Future Research Directions 419
16.7 Conclusion 421

17 Artificial Intelligence's Ethical Consequences: Difficulties, Hazards, and Regulatory Viewpoints 425
Anita Pati Mishra, Mani Dublish and Shailender Kumar Vats

17.1 Introduction 426
17.2 Mapping the Research Environment 427
17.3 Digital Transformation, the Dangers of AI, and Ethical Concerns in Research Settings 428
17.4 Research Theories and Conceptual Framework 430
17.5 Privacy, Reliability, and Cognitive Preparedness 432
17.6 Results 435
17.7 Analysis and Discussion 437
17.8 Conclusions 439

18 Technical Challenges and System Limitations 447
Sachin Jain, Vishal Jain, Danish Ather, Golnoosh Manteghi and Abu Bakar Abdul Hamid

18.1 Introduction 448
18.2 Literature Review: A Landscape of Distributed Challenges 451
18.3 Conceptual Models and Mathematical Formulations 455
18.4 Descriptive Visualizations of System Limitations 458
18.5 Case Studies: Challenges in Real-World Application 458
18.6 System-Level Limitations and Future Research Directions 461
18.7 Conclusion 463

19 Trust by Design: AI's Evolution in Secure and Transparent Data Systems 467
Nandini Srivastava and Anuradha M. Dhumale

19.1 Introduction 468
19.2 Evolution of AI in Data Security and Transparency 470
19.3 Machine Learning 477
19.4 Trust in AI 482
19.5 Comparison Table and Use Cases 484
19.6 Conclusion 488

20 Decentralized Intelligence: Redefining Learning through Secure AI and EoT Integration 491
Ravipalli Sri Santhi Nehru'

20.1 Introduction 492
20.2 Conceptual Foundations 494
20.3 Architecture of the Decentralized Learning Ecosystem 496
20.4 Foundational Technologies for Privacy-Preserving, Distributed Education 497
20.5 Applications and Use Cases 498
20.6 Issues Related to the Technology and Their Solutions 500
20.7 Social, Policy, and Ethical Aspects 502
20.8 New Technologies and What to Expect in the Future 503
20.9 Conclusion 505

21 Fortifying Financial Systems: Privacy-Centric Collaborative Detection with Transparent Accountability 509
Jarnail Singh and Shelley Khosla

21.1 Introduction 510
21.2 Literature Review 511
21.3 Methodology 514
21.4 Experimental Setup 516
21.5 Results 518
21.6 Discussion 520
21.7 Challenges and Future Directions 520
21.8 Conclusion 521

Abbreviations 522
References 523
Index 527