AI-Driven National Cyber Defense and Resilience Strategies

The acceleration of the digital transformation of critical infrastructure, government services, and military systems has profoundly changed the cyber threat landscape. Governments now face cyber risks of unprecedented scale and sophistication, ranging from advanced persistent threats (APTs) and AI-assisted cyber espionage to large-scale ransomware campaigns, hybrid cyber-physical attacks, and information influence operations. In this context, traditional and reactive approaches to cybersecurity are no longer sufficient to ensure effective national cyber defense and resilience. AI-Driven National Cyber Defense and Resilience Strategies offers an in-depth, forward-looking analysis of how artificial intelligence; specifically, machine learning, deep learning, and generative AI; can be leveraged to strengthen national cyber defense capabilities. The book explores the role of AI in improving threat intelligence, intrusion detection, incident response, cyber deception, security orchestration, and large-scale decision support, while highlighting the new risks posed by adversaries themselves equipped with advanced AI capabilities. Bringing together contributions from researchers, industry experts, and institutional decision-makers, this book presents cutting-edge methodologies, innovative architectural frameworks, and concrete use cases from national security operations centers (SOCs), incident response teams (CSIRTs), military cyber commands, and critical infrastructure operators. Particular attention is given to the concepts of AI-driven cyber resilience, including adaptive defense, autonomous response, cyber situational awareness, and collaborative intelligence sharing at the national and international levels. Beyond technological advances, the book critically examines the issues of governance, ethics, trust, and regulation related to the deployment of artificial intelligence in contexts of digital sovereignty and national defense. By bringing together technical innovations, strategic considerations, and regulatory frameworks, this volume is a leading reference for researchers, practitioners, and decision-makers seeking to design resilient, secure, and trustworthy national cyber defense ecosystems in the age of artificial intelligence.

Prof. Mounia Zaydi is an Associate Professor of Cybersecurity at JUNIA ISEN Engineering School and a researcher at the Interdisciplinary Laboratory of Transitions of the Catholic University of Lille, France. She is a member of IEEE and the International Association of Engineers (IAENG). Her research focuses on information security and privacy, network and IoT security, IT governance, risk management, and the application of artificial intelligence to cybersecurity operations, incident response, and digital transformation. Her work particularly addresses the role of AI in enhancing security agility, threat detection, and resilience within complex information systems. Prof. Zaydi has authored and co-authored numerous peer-reviewed publications, including journal articles and book chapters, and actively contributes to the academic community as a reviewer and member of executive and technical program committees for international conferences and journals.

Prof. Yassine Maleh is an Associate Professor of Cybersecurity and IT Governance at Sultan Moulay Slimane University, Morocco. He is the founding chair of the IEEE Consultant Network Morocco and the founding president of the African Research Center of Information Technology & Cybersecurity. He is a Senior Member of IEEE and a member of IAENG and the Machine Intelligence Research Labs. His research activities focus on information security and privacy, Internet of Things security, wireless and constrained networks, and IT governance. He has authored and edited numerous scholarly works, including journal articles, conference papers, and books, and is widely recognized for his contributions to cybersecurity research and knowledge dissemination. Maleh holds several key editorial roles, including Editor-in-Chief and Associate Editor positions in leading international journals, and serves as a series editor for academic book collections in cybersecurity management. He is actively involved in the organization of international conferences and regularly contributes as a reviewer and program committee member for high-impact journals and conferences. His academic leadership and service activities have significantly contributed to advancing cybersecurity research at both regional and international levels.

Prof. Hayat Zaydi is a Professor of Computer Science at the National Superior School of Mines of Rabat (ENSMR), Morocco. She is a Cisco Academy Instructor and a member of the International Association of Engineers (IAENG). Her research spans the Internet of Things, with a particular emphasis on healthcare-oriented applications, as well as artificial intelligence and distributed computing paradigms such as edge, fog, and cloud computing. A central focus of her work lies in the design of secure and resilient data-driven architectures integrating machine learning and deep learning techniques, especially within Internet of Medical Things (IoMT) environments. Zaydi has published extensively in international journals, conferences, and edited volumes. She is actively engaged in the academic community through her participation in technical program committees and as a reviewer for numerous international scientific venues. Her work bridges advanced computing architectures, AI, and cybersecurity to address emerging challenges in smart and healthcare systems.

Prof. Youness Khourdifi is a Professor and Researcher in Computer Science at Sultan Moulay Slimane University, Morocco, where he teaches at the Faculty of Polydisciplinary Studies of Khouribga. He is an active member of the Laboratory of Material Sciences, Mathematics, and Environment (LS2ME) and is affiliated with professional organizations including IEEE, ACM, IAENG, and Fondation Maroc Numérique. His research interests lie at the intersection of artificial intelligence, data engineering, and healthcare technologies. His work includes database migration and interoperability, particularly the automation of relational-to-NoSQL transformations, as well as the application of deep learning techniques to medical data analysis. He also investigates issues related to information security, IoT security, big data, and intelligent systems. Khourdifi has authored numerous scientific publications and actively contributes to the research community as a reviewer and program committee member in the fields of artificial intelligence and data science. Through his academic and organizational activities, he promotes interdisciplinary collaboration and the practical application of advanced computational methods to real-world challenges.