Preface xvii
Hemant Kumar SAINI, Mariya OUAISSA, Yassine MALEH, Mariyam OUAISSA and Rejwan BIN SULAIMAN

About the Editors xxi
Hemant Kumar SAINI, Mariya OUAISSA, Yassine MALEH, Mariyam OUAISSA and Rejwan BIN SULAIMAN

Chapter 1. Privacy-preserving ML and Secure AI Architectures 1
Hicham ZMAIMITA, Abdellah MADANI and Driss ABADA

1.1. Introduction 1
1.2. Threat model and leakage taxonomy. 3
1.3. Privacy-by-design requirements for secure GenAI architectures 6
1.4. Reference architecture 8
1.5. Securing file ingestion 15
1.6. Architecture-wide data protection (condensed) 18
1.7. Secure RAG and connector safety 20
1.8. Runtime controls and operations 21
1.9. Evaluation methodology and key metrics 22
1.10. Deployment guidance and checklist 23
1.11. Conclusion and outlook 23
1.12. References 25

Chapter 2. Shadow AI, Insider Threats and Organizational Uploaded Risks 29
Shahed A. AL-TAMIMI and Qasem Abu AL-HAIJA

2.1. Introduction 29
2.2. History of Shadow AI and fundamental concept 35
2.3. Insider threats 36
2.4. Organizational uploaded risks 44
2.5. Threat modeling for Generative AI systems 45
2.6. Case studies 47
2.7. Open challenges 48
2.8. Mitigating Shadow AI and insider threats: policies, governance and human factors 49
2.9. Conclusion and future work 53
2.10. References 53

Chapter 3. Mitigating Data Leakage in Gen-AI Cloud Uploads: Detection Frameworks and Best Practices 57
Lourdu Akhila YERUVA, Shubneet and Anushka Raj YADAV

3.1. Introduction 58
3.2. Foundations of Gen-AI cloud uploads for data protection 61
3.3. Semantic DLP for Gen-AI prompts 63
3.4. File and multimodal upload inspection 66
3.5. Real-time risk scoring and policy evaluation 70
3.6. Data preparation, encoding and false-positive management 73
3.7. Compliance and regulatory risks of Gen-AI cloud uploads 77
3.8. Advanced hybrid and privacy-preserving enforcement 79
3.9. Case studies and pilots of Gen-AI upload protection 83
3.10. Conclusion 88
3.11. References 89

Chapter 4. Threat Modeling for Upload-Induced Data Leakage in Generative AI 95
Nikita SHARMA, Bindiya JAIN, Hemlata JAIN and Manisha GAUR

4.1. Introduction 95
4.2. System model: upload-driven generative AI architecture 97
4.3. Formal definition and taxonomy of upload-induced data leakage 101
4.4. Adversary model 106
4.5. Threat modeling framework for upload-induced leakage 110
4.6. Quantitative risk assessment framework for upload-induced leakage 114
4.7. Mitigation mapping: from leakage threats to defensive controls 117
4.8. Regulatory and compliance implications 121
4.9. Conclusion 122
4.10. References 124

Chapter 5. Secure Threat Modeling of Upload-based Data Leakage in Generative AI Systems 127
Shahed A. AL-TAMIMI and Qasem Abu AL-HAIJA

5.1. Introduction 127
5.2. Fundamental background 131
5.3. Data leakage cyber threat 134
5.4. Upload-induced data leakage within Generative AI 140
5.5. Threat modeling for Generative AI systems 142
5.6. Risk assessment and mitigation. 145
5.7. Open challenges 148
5.8. Conclusion and future work. 149
5.9. References 150

Chapter 6. Uncontrolled Generative AI Uploads and Sector-Specific Data Leakage: A Statistical Case Study Across Healthcare, Finance, Legal and Software Domains 155
N. MANI, V. KAVITHA and B.L. SHIVAKUMAR

6.1. Introduction 156
6.2. Theoretical and statistical framework 158
6.3. Case study I: healthcare industry 162
6.4. Case study II: financial services 166
6.5. Case study III: legal sector 169
6.6. Case study IV: software and technology industry 172
6.7. Risk severity matrix 175
6.8. An integrative statistical risk-scoring framework 178
6.9. Implications of policy and governance 181
6.10. Conclusion 184
6.11. References 185

Chapter 7. Role of Digital Forensics Techniques in Sustaining Generative AI Systems 189
Muhammad Ahsan QURESHI

7.1. Introduction 189
7.2. Foundations: digital forensics and AI ecosystems 191
7.3. Role of AI in digital forensics 195
7.4. Forensic readiness in GenAI systems 199
7.5. Evidence sources in GenAI ecosystems 202
7.6. Acquisition and preservation in AI environments 205
7.7. AI-powered tools and technologies in digital forensics 208
7.8. Advanced forensic analysis for GenAI 211
7.9. Sustaining GenAI systems through continuous forensic assurance 213
7.10. Legal, ethical and governance considerations 215
7.11. The future of AI in digital forensics 218
7.12. Conclusion 219
7.13. References 220

Chapter 8. Forensic-Driven Security for Generative AI Detecting Upload-Induced Data Leakage 223
Mritunjay Kr. RANJAN, Parimala MANI, Pranjal SONJE, Rajashri RIKAME, Disha ARSUDE and Ankita PATIL

8.1. Introduction 224
8.2. Related study 226
8.3. Problem statement 228
8.4. Methodology 230
8.5. System architecture 236
8.6. Results and discussion 238
8.7. Conclusion 243
8.8. Future work 244
8.9. References 244

Chapter 9. DeepFakeGuard: A Multimodal Framework for Detecting Misinformation Driven by GenAI Data Leakage 247
Bayan ALFARRAYEH, Mais ALASHQAR, Marya SABEHA, Farah Abu AL-SOUD and Qasem Abu AL-HAIJA

9.1. Introduction 247
9.2. The deepfake threat landscape 250
9.3. Related work and research gaps 253
9.4. Datasets and generator artifacts 258
9.5. DeepFakeGuard system architecture 261
9.6. Transformer-based text deepfake detection 267
9.7. Multimodal fusion and decision strategy 271
9.8. Cybersecurity and societal implications 275
9.9. Evaluation strategy performance validation 277
9.10. Limitations and future directions 279
9.11. Conclusion 281
9.12. References 281

Chapter 10. A Post-Quantum Secure Automata-Governed Framework for Preventing Upload-Induced Data Leakage in Generative AI Systems Using Lattice Cryptography 283
Rohit GUPTA, Amit KUMAR, Shilpa BHOJNE, Jyotsna KULKARNI, Ankita PATIL and Mritunjay Kr. RANJAN

10.1. Introduction 284
10.2. Related study 285
10.3. Problem statement 287
10.4. Methodology 288
10.5. System architecture 298
10.6. Results and discussion 299
10.7. Conclusion 302
10.8. Future work 303
10.9. References 303

Chapter 11. An Automata-Governed Self-Healing Cybersecurity Architecture Integrating Machine Learning and Upgradeable Blockchain Smart Contracts 307
Pankaj PATIL, Mritunjay Kr. RANJAN, Monali JADHAV, Jayashree KUNDE, Ishwari RAKIBE and Disha ARSUDE

11.1. Introduction 308
11.2. Related study 309
11.3. Problem statement 312
11.4. Methodology 314
11.5. System architecture 322
11.6. Results and discussion 323
11.7. Conclusion 326
11.8. Future work 327
11.9. References 328

Chapter 12. A Privacy-Aware Hybrid Automata–Machine Learning Framework for Secure Real-Time Fraud Detection in Satellite-enabled Financial Systems 331
Vivek NAKHATE, Mritunjay Kr. RANJAN, Sarika KONDEKAR, Gaurav PATIL, Rajashri RIKAME and Pranjal SONJE

12.1. Introduction 331
12.2. Related study 333
12.3. Problem statement 335
12.4. Methodology 335
12.5. System architecture 344
12.6. Results and discussion 345
12.7. Conclusion 348
12.8. Future work 349
12.9. References 349

Chapter 13. Mitigating Gen-AI Upload-induced Data Leakage with Federated TinyML on ESP32: A Privacy-Preserving Edge Architecture for Rural Biogas Production Forecasting 353
Amine CHIGUER, Mohammed SADIK and Abderrahim FAIL

13.1. Introduction 354
13.2. Materials and methods 356
13.3. Results 361
13.4. Discussion. 366
13.5. Conclusion 371
13.6. References 372

List of Authors 377
Index 383