This comprehensive book explores the rapidly evolving field of artificial intelligence and emerging technologies in cybersecurity.

It covers fundamental concepts, key terminologies, and advanced machine learning algorithms used for security applications.

Readers will gain insights into data preparation, feature engineering, and model validation processes, alongside ethical considerations and bias mitigation strategies.

The book maps AI capabilities to major security frameworks such as NIST and ISO, and discusses automation of security operations with AI-driven tools.

Through detailed case studies, it highlights AI-enhanced security incident response, vulnerability scanning, threat intelligence, and red team exercises.

It also offers guidance on cybersecurity certifications, certification exam preparation, and staying compliant with regulatory standards.

Additionally, the book delves into sophisticated topics like adversarial attacks on AI models, deploying AI in real-time threat monitoring, securing IoT devices, and integrating blockchain and cloud security solutions.

Practical hands-on techniques, operational challenges, and best practices for developing, deploying, and maintaining AI security systems are emphasized.

Designed for cybersecurity professionals, students, and researchers, this book provides an in-depth resource for leveraging AI to enhance security posture and drive technological innovation in cybersecurity.