Guide to AI for Cybersecurity: Principles, Frameworks, and Practical Implementation

With cybercrime costs exceeding $10.5 trillion annually and ransomware attacks predicted every two seconds by 2031, traditional signature-based security has reached critical breaking points. Guide to AI for Cybersecurity provides the essential roadmap for harnessing artificial intelligence as a force multiplier against sophisticated, AI-powered threats. This comprehensive textbook bridges the gap between artificial intelligence theory and practical cybersecurity applications through 18 chapters organized around an innovative detection, response, prediction, and prevention (DRPP) framework. Drawing from recent high-impact incidents--including the 2025 Collins Aerospace cyberattack, the Marks & Spencer ransomware attack, and the Co-op data breach --readers progress from foundational concepts to advanced implementations, gaining hands-on experience with production-ready code examples, real-world case studies, and comprehensive deployment guidance for AI-powered security solutions. Topics and features: - - - - - This essential textbook/guide provides comprehensive coverage suitable for graduate students in computer science, cybersecurity, or AI/ML programs, as well as cybersecurity professionals seeking to master AI-powered defense techniques. Software architects building secure AI systems, academic instructors developing AI security courses, and researchers investigating adversarial machine learning also will find the volume invaluable. Muthu Ramachandran is Research Consultant at Forti5 Technologies Ltd, UK, and Visiting Professor Extraordinarius at University of South Africa.