Full Description
With ransomware attacks predicted every two seconds by 2031 and 91% of successful cyberattacks beginning with social engineering, organizations face existential threats that demand AI-powered defenses integrating both technical sophistication and human behavioral insights.
This comprehensive textbook bridges cutting-edge AI research with practical cybersecurity implementation. Readers progress from specialized applications including quantum-resistant architectures and AI-blockchain integration, through ethical governance and accountability frameworks, to advanced defense techniques and societal applications addressing threats from cyberbullying to AI-powered disinformation. The text uniquely integrates cognitive psychology with AI techniques, providing frameworks for human-AI collaborative defense that strengthen rather than replace human capabilities.
Topics and features:
• Introduces post-quantum cryptography and quantum-resistant AI security frameworks for the coming cryptographic transition
• Includes complete instructor resources with slides, exercises, and assessments
• Covers Model Context Protocol (MCP) security and LLM security for emerging AI agent architectures
• Presents neurosymbolic AI approaches combining neural networks with symbolic reasoning for enhanced threat detection
• Addresses global governance strategies with regulatory compliance guidance for GDPR, AI Act, and CCPA
• Features psychological resilience-building and behavioral analytics
This essential volume provides comprehensive coverage suitable for graduate students in computer science, cybersecurity, AI, or software engineering programs. Security professionals, software architects, academic instructors, and technology leaders responsible for AI governance will find the frameworks and implementations invaluable for advancing practice in this critical field.
Muthu Ramachandran is Research Consultant at Forti5 Technologies Ltd, UK, and Visiting Professor Extraordinarius at University of South Africa.
Contents
.- Introduction.
.- Modern Threat Landscape and AI Opportunities.
.- Cybersecurity Frameworks in the AI Era.
.- AI Security Architecture and Infrastructure.
.- Machine Learning for Threat Detection.
.- Advanced Analytics and Threat Intelligence.
.- Implementation Case Studies.
.- AI-Enhanced Secure Software Development Lifecycle.
.- Application Security with Machine Learning.
.- Data Protection and Privacy in AI Systems.
.- Automated Incident Response and Orchestration.
.- AI Security and Adversarial Defences.
.- Future Directions and Emerging Threats.
