TABLE OF CONTENTS AI-Enabled Cyber Threats: The Rise of Artificial Intelligence in Cyber Crime. i Chapter 1. 1 Introduction to AI-Enabled Cyber Threats. 1 Abstract 1 Keywords. 1 1.1 The Convergence of AI and Cybersecurity. 1 1.2 Historical Evolution of Cyber Threats.

3 1.3 The AI Revolution in Cyber Crime. 5 1.4 Defining AI-Enabled Threats. 7 1.5 Scope and Scale of the Problem. 8 1.6 Current Threat Landscape.

10 1.7 Objectives of This Book. 12 1.8 Target Audience and Structure. 13 1.9 Terminology and Conventions. 16 1.10 Looking Ahead.

17 References. 18 Chapter 2. 21 Fundamentals of AI/ML in Cybersecurity Context. 21 Abstract 21 Keywords. 21 2.1 Machine Learning Basics. 21 2.2 Supervised Learning Algorithms.

23 2.3 Unsupervised Learning Algorithms. 25 2.4 Deep Learning and Neural Networks. 27 2.5 Natural Language Processing. 30 2.6 Computer Vision and GANs.

32 2.7 Reinforcement Learning. 35 2.8 AI in Offensive Cybersecurity. 37 2.9 AI in Defensive Cybersecurity. 39 2.10 Code Examples and Implementations.

41 References. 44 Chapter 3. 47 AI-Enhanced Attack Vectors. 47 Abstract 47 Keywords. 47 3.1 AI-Generated Phishing and Social Engineering. 47 3.2 Large Language Models in Cybercrime.

50 3.3 Spear-Phishing Automation. 53 3.4 Deepfake Technology. 56 3.5 Voice Cloning Attacks. 60 3.6 Detection Evasion Techniques.

64 3.7 Case Studies and Statistics. 67 References. 71 Chapter 4. 75 AI POWERED MALWARE AND RANSOMWARE. 75 Abstract 75 Keywords. 75 4.1 Polymorphic Malware Using ML.

75 4.2 Adversarial Machine Learning for Evasion. 80 4.3 AI-Generated Code Obfuscation. 84 4.4 Ransomware-as-a-Service with AI. 88 4.5 Automated Vulnerability Exploitation.

93 4.6 Major Ransomware Campaigns. 98 4.7 Malicious AI Tools and Frameworks. 103 References. 108 Chapter 5. 111 ADVERSARIAL MACHINE LEARNING ATTACKS RANSOMWARE. 111 Abstract 111 Keywords.

111 5.1 Data Poisoning and Backdoor Attacks. 111 5.2 Evasion Attacks and Adversarial Examples. 114 5.3 Model Inversion and Privacy Attacks. 118 5.4 Model Extraction and Stealing.

120 5.5 Prompt Injection and LLM Attacks. 123 5.6 AI System Vulnerabilities. 126 5.7 Defense Mechanisms. 128 References. 131 Chapter 6.

133 REAL-WORLD CASE STUDIES AND FORENSIC ANALYSIS. 133 Abstract 133 Keywords. 133 6.1 MGM Resorts Cyberattack. 133 6.2 Colonial Pipeline Ransomware. 137 6.3 Arup Engineering Deepfake Fraud.

138 6.4 Colonial Pipeline: Extended Analysis. 139 6.5 Arup Engineering Deepfake Fraud: Extended Analysis. 142 6.6 SolarWinds Supply Chain Attack. 145 6.7 Healthcare Sector Attacks: Extended Analysis.

146 6.8 Financial Sector Incidents: Extended Analysis. 149 6.9 Threat Actor Profiles and TTPs. 150 References. 152 Chapter 7. 155 DEFENSIVE AI TECHNOLOGIES AND COUNTERMEASURES. 155 Abstract 155 Keywords.

155 7.1 Machine Learning-Based Threat Detection. 155 7.2 Anomaly Detection Algorithms. 158 7.3 Behavioral Analytics and UEBA. 160 7.4 Network Traffic Analysis (AI/ML Approaches) 162 7.

5 AI-Powered IDS/IPS Systems. 163 7.6 Automated Threat Hunting. 165 7.7 SIEM and SOAR with AI. 167 7.8 Zero-Trust Architecture. 168 7.

9 Deception Technologies. 171 7.10 Real-World Implementations. 172 References. 174 Chapter 8. 179 TECHNICAL IMPLEMENTATION - CODE EXAMPLES AND FRAMEWORKS. 179 Abstract 179 Keywords. 179 8.

1 TensorFlow for Cybersecurity. 179 8.2 PyTorch for Threat Detection. 181 8.3 Scikit-learn for Security Analytics. 183 8.4 Building AI-Powered IDS. 184 8.

5 Implementing Behavioral Analytics. 187 8.6 Automated Response Systems. 189 8.7 Adversarial Training. 190 8.8 Model Hardening Techniques. 192 8.

9 Explainable AI for Security. 193 8.10 MLOps for Security Deployment 195 References. 197 Chapter 9. 201 POLICY, ETHICS, AND GOVERNANCE. 201 Abstract 201 Keywords. 201 9.1 Regulatory Frameworks.

201 9.2 NIST AI Risk Management Framework (RMF) 202 9.3 EU AI Act Implications. 204 9.4 Ethical Considerations in AI-Enabled Cyber Operations. 206 9.5 Bias and Fairness in AI Security Systems. 208 9.

6 Privacy and Data Protection: GDPR, CCPA, and Beyond. 209 9.7 Accountability and Transparency in AI Systems. 211 9.8 AI Governance Framework for Cybersecurity. 212 9.9 International Cooperation and Agreements. 214 9.

10 Industry Best Practices and Self-Regulation. 215 References. 217 Chapter 10. 221 FUTURE TRENDS AND EMERGING THREATS. 221 Abstract 221 Keywords. 221 10.1 The Quantum Computing Threat to Cryptography. 222 10.

2 Post-Quantum Cryptography (PQC) and the Transition. 224 10.3 Next-Generation AI Attacks: Swarm Intelligence and Self-Evolving Malware. 227 10.4 The Rise of Autonomous AI Agents in Cyber Warfare. 229 10.5.