AI-Enabled Cyber Threats:

The Rise of Artificial Intelligence in Cyber Crime
1. Auflage 2026
ISBN: 978-1-394-41694-3
Verlag: John Wiley & Sons Inc

Buch, Englisch, 240 Seiten

Understand AI-driven cyberattacks and build effective defensive strategies against them

Artificial intelligence is increasingly used to automate, enhance, and evolve cyberattacks, yet most existing resources address AI only as a defensive tool. AI-Enabled Cyber Threats: The Rise of Artificial Intelligence in Cyber Crime delivers a full-spectrum analysis of AI's dual role in cybersecurity, covering offensive techniques, adversarial AI methods, and countermeasures from technical, ethical, and societal perspectives for professional and academic audiences.

AI-Enabled Cyber Threats balances theoretical foundations with actionable defensive strategies. It examines the sophisticated methods malicious actors employ using AI, from autonomous AI hackers to AI-powered nation-state warfare. The book addresses the dual-use nature of AI technologies, equipping readers to design stronger defenses, understand adversarial AI techniques, and lead security innovations responsibly in an AI-dominant threat landscape.

The book also provides: - Analysis of how AI automates and evolves cyberattack methodologies, including practical threat examples drawn from real-world offensive scenarios
- Defensive frameworks and countermeasures developed by security professionals and institutions to mitigate AI-driven threats across organizations
- Coverage of ethical considerations and societal impacts arising from the weaponization of artificial intelligence in cyber crime
- Future-facing insights on emerging risks including autonomous AI hackers and AI-powered nation-state cyber warfare campaigns
- Guidance for building proactive, adaptive cybersecurity strategies that anticipate threats rather than relying on traditional reactive approaches

Designed for cybersecurity professionals, AI researchers, and graduate students studying adversarial machine learning or cybercrime and digital forensics, this book provides the technical depth and strategic perspective needed to understand and counter AI-driven threats. Risk managers and compliance professionals will also find useful frameworks for organizational defense.

Autoren/Hrsg.

Dommari, Sandeep

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering

Inhaltsverzeichnis

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 Securing the Convergence: AI in IoT, Edge, 5G, and 6G Networks. 230

10.6 The Role of Blockchain in Future Cybersecurity Architectures. 232

10.7 Nation-State Cyber Warfare in the AI Era. 233

10.8 Predictions for the Cyber Threat Landscape (2025-2030) 235

10.9 Conclusion: Recommendations for Organizational Resilience. 236

References. 238

Über Autor(innen)

Sandeep Dommari is a recognized Cybersecurity, IAM, and AI leader with over 18 years of experience. Currently serving as a Principal Cybersecurity Architect, he designs scalable, secure digital ecosystems that protect millions globally.

Throughout his career across the public and private sectors, Sandeep has spearheaded large-scale IAM transformations and AI-driven threat detection initiatives. A passionate advocate for ethical AI and zero-trust security, he bridges cutting-edge technology with practical enterprise needs to develop proactive, resilient architectures.

His mission is to build secure, trusted digital environments that serve both business and society.