Al and Cybersecurity: Innovations in Threat Detection and Prevention explores the intersection of Artificial Intelligence (AI) and cybersecurity in the context of modern threats. As the frequency and complexity of cyberattacks grow, traditional methods of defense are becoming insufficient, making Al-driven solutions increasingly essential. This book provides an in-depth look at how Al is transforming the way cybersecurity systems detect, prevent, and respond to threats in real-time. Through detailed analysis, case studies, and practical examples, this book covers the wide-ranging applications of Al in cybersecurity, from Al-powered threat hunting to machine learning-based anomaly detection and automated incident response systems.
Readers will gain a deep understanding of the latest Al algorithms, the role of predictive security, and the ethical and regulatory challenges that come with implementing Al in cybersecurity. The book also addresses key challenges in scaling Al security solutions, examining how to integrate Al with existing infrastructure and the need for continuous learning. By offering both technical insights and a forward-looking perspective on future trends, Al and Cybersecurity is a valuable resource for cybersecurity professionals, technologists, and students eager to understand the future of Al in securing digital ecosystems.