AI-Driven Security: Navigating Threats and Defenses in a New Era - Couverture rigide

AlQahtani, Ali Abdullah S.; Khan, Muhammad Khurram

Couverture rigide

ISBN 10 : 1394371217 ISBN 13 : 9781394371211

Editeur : Wiley-IEEE Press, 2026

Synopsis

Leverage AI for adaptive cyber defense against evolving threats

Artificial intelligence simultaneously strengthens cyber defenses and introduces new attack vectors such as adversarial exploits and AI-driven malware. AI-Driven Security: Navigating Threats and Defenses in a New Era, written by two cybersecurity researchers specializing in digital authentication and information assurance, examines this dual role by integrating machine learning, deep learning, and generative AI across networks, endpoints, IoT, and autonomous systems.

AI-Driven Security covers real-time network traffic analysis and anomaly detection, insider threat identification through pattern analysis, and AI-assisted incident response that reduces delays. The book examines adversarial attacks on AI systems and strategies for building resilient defenses. It also addresses ethical dimensions including privacy, bias and fairness, and accountability alongside regulatory and societal considerations.

Readers will also find:

• Real-world case studies illustrating how AI accelerates detection and mitigation during cyber incidents across diverse operational environments
• Coverage of emerging technologies including 6G networks, quantum computing challenges, and blockchain integration with privacy-enhancing security frameworks
• Strategies for defending against adversarial attacks targeting AI models and securing machine learning pipelines from exploitation
• Analysis of ethical issues in AI-driven security spanning bias, fairness, transparency, and accountability in automated decision-making
• Forward-looking perspectives on generative AI, reinforcement learning, and their roles in proactive threat prediction and response

Designed for cybersecurity professionals, AI researchers, and policymakers, this book connects threat detection automation with broader defense frameworks and ethical governance. Students and academics in AI and cybersecurity programs will also find structured, research-grounded coverage of both offensive and defensive AI applications.

A propos du livre

À propos de l'auteur

ALI ABDULLAH S. ALQAHTANI, PhD, is an Assistant Professor and Founding Director of the Defense Research Lab at Prince Sultan University, Riyadh, Saudi Arabia. His research advances zero-effort digital authentication, threat identification, IoT, AI, and ML. He has secured over $6.7M in funded grants as a Principal Investigator.

MUHAMMAD KHURRAM KHAN, PhD, is a global cybersecurity thought leader and Professor at King Saud University, Saudi Arabia. He is Founder and CEO of the Global Foundation for Cyber Studies and Research (USA), and Editor-in-Chief of Telecommunication Systems (Springer Nature). He has published over 500 research papers and holds 12 registered US patents.

MOHAMED HAMMAD, PhD, is an Associate Professor at Menoufia University, Egypt, and a Researcher at Prince Sultan University, Saudi Arabia. His work focuses on pattern recognition, AI, and cybersecurity. He has published 50+ SCI papers, edited five books, and is a top 2% cited scientist (Stanford, 2022–2025).

À propos de la quatrième de couverture

Leverage AI for adaptive cyber defense against evolving threats

Artificial intelligence simultaneously strengthens cyber defenses and introduces new attack vectors such as adversarial exploits and AI-driven malware. AI-Driven Security: Navigating Threats and Defenses in a New Era, written by two cybersecurity researchers specializing in digital authentication and information assurance, examines this dual role by integrating machine learning, deep learning, and generative AI across networks, endpoints, IoT, and autonomous systems.

AI-Driven Security covers real-time network traffic analysis and anomaly detection, insider threat identification through pattern analysis, and AI-assisted incident response that reduces delays. The book examines adversarial attacks on AI systems and strategies for building resilient defenses. It also addresses ethical dimensions including privacy, bias and fairness, and accountability alongside regulatory and societal considerations.

Readers will also find:

• Real-world case studies illustrating how AI accelerates detection and mitigation during cyber incidents across diverse operational environments
• Coverage of emerging technologies including 6G networks, quantum computing challenges, and blockchain integration with privacy-enhancing security frameworks
• Strategies for defending against adversarial attacks targeting AI models and securing machine learning pipelines from exploitation
• Analysis of ethical issues in AI-driven security spanning bias, fairness, transparency, and accountability in automated decision-making
• Forward-looking perspectives on generative AI, reinforcement learning, and their roles in proactive threat prediction and response

Designed for cybersecurity professionals, AI researchers, and policymakers, this book connects threat detection automation with broader defense frameworks and ethical governance. Students and academics in AI and cybersecurity programs will also find structured, research-grounded coverage of both offensive and defensive AI applications.

Détails de l'édition

• Éditeur: Wiley-IEEE Press
• Date d'édition: 2026
• Langue: anglais
• ISBN 10: 1394371217
• ISBN 13: 9781394371211
• Reliure: Gebundene Ausgabe
• Numéro d'édition: 1
• Nombre de pages: 224
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible