Al and Cybersecurity: Advancements in Threat Detection and Prevention is a comprehensive exploration of the transformative role artificial intelligence plays in modern cybersecurity practices. The book offers an in-depth analysis of the ways Al is being used to combat the rising tide of cyber threats, with a particular focus on advancements in threat detection and prevention. It provides readers with a detailed overview of Al techniques such as machine learning, natural language processing, and neural networks, demonstrating how these technologies are enhancing the accuracy, efficiency, and scalability of cybersecurity measures.
The book is structured to address both the theoretical underpinnings and practical applications of Al in cybersecurity. It covers key topics like anomaly detection, intrusion detection systems, predictive analytics, and threat intelligence. Each chapter is supported by real-world case studies and examples, showing how Al is being deployed to safeguard critical infrastructure across industries such as finance, healthcare, and government. The authors also discuss emerging challenges in Al security, including ethical concerns, adversarial Al, and the need for continuous adaptation to new threat vectors. With contributions from leading experts, this book is an essential guide for anyone looking to understand and harness the power of Al in the fight against cybercrime.