AI-Driven Cybersecurity for Autonomous Systems

AI-driven cybersecurity for autonomous systems protects intelligent, automated technologies from cyber threats, such as autonomous vehicles, drones, and industrial robots. As these systems become integrated into infrastructure, their reliance on real-time data processing, machine learning, and network connectivity makes them vulnerable to attacks. AI-driven cybersecurity offers proactive defense mechanisms by using algorithms that can detect anomalies, predict threats, and respond to intrusions faster than traditional methods. This approach enhances the resilience and safety of autonomous systems while ensuring their reliability in high-stakes environments. AI-Driven Cybersecurity for Autonomous Systems explores the intersection of cybersecurity, AI, and robotics, addressing technological advancements, ethical dilemmas, and risk mitigation strategies. It examines theoretical frameworks, practical applications, and policy implications, with a focus on securing AI-driven robotic systems in critical sectors like healthcare, defense, and smart cities. This book covers topics such as risk mitigation, robotics, and threat detection, and is a useful resource for security professionals, computer engineers, academicians, researchers, and data scientists.

Toufik Mzili is a professor and researcher in Artificial Intelligence and Optimization at Chouaib Doukkali University, Morocco. He holds a Ph.D. in computer science and specializes in combinatorial optimization and computational intelligence. His research focuses on hybrid metaheuristic and machine learning approaches for solving large-scale NP-hard problems, including QAP and scheduling. He has published in high-impact journals and serves as an Associate Editor and reviewer for leading scientific venues. His interests include hybrid AI–optimization systems, swarm intelligence, fuzzy optimization, and intelligent applications in healthcare and industry.

Zahra Oughannou an Assistant Professor at Ibn Zohr University. Received her Professional Degree in Mobile Application Engineering from Higher School of Technology, Salé, and her Master's in Information Systems Security from Ibn Tofail University, Kenitra. She completed her Ph.D. in Computer Science at Ibn Tofail University in 2023. Her research focuses on IoT security, real-time data analysis, and smart university systems. Dr. Oughannou has published several papers in international conferences and journals and has served as a reviewer for scientific articles.

Nebojsa Bacanin received his Ph.D. degree from the Faculty of Mathematics, University of Belgrade, in 2015 (study program Computer Science, average grade 10,00). He started his university career in Serbia 18 years ago at the Graduate School of Computer Science in Belgrade. He currently works as Full Professor, Vice-Rector for Scientific Research and Head of Applied Artificial Intelligence study program at Singidunum University, Belgrade, Serbia. He is involved in scientific research in the field of computer science, and his specialty includes stochastic optimization algorithms, swarm intelligence, soft-computing, optimization, and modeling, as well as artificial intelligence algorithms, swarm intelligence, machine learning, image processing, and cloud and distributed computing. He has published more than 430 scientific papers (more than 180 SCIE papers) in high-quality journals and international conferences indexed in Clarivate Analytics JCR, Scopus, WoS, IEEExplore, and other scientific databases. As member of numerous Editorial boards in cutting-edge international journals and Committee boards of international conferences, he regularly edit and perform review activities. He has also been included in the prestigious Stanford University list of the 2% best world researchers, when the whole career is considered, in the field of Artificial Intelligence. Also, according to AD scientific index, he is currently listed as the best researcher from Computer Science area in Serbia.

Widi Aribowo as an Assistant Professor in the Department of Electrical Engineering at the Faculty of Vocational Studies, Surabaya State University. Known as a leading researcher, he has made significant contributions in the fields of metaheuristics, optimization, artificial intelligence, power systems and Microgrid. His scientific impact is evident through various publications in leading journals. In addition, Widi Aribowo has demonstrated his expertise as a peer reviewer for several prestigious Q1 journals, demonstrating his commitment to advancing academic discourse in the fields of metaheuristics, optimization, artificial intelligence, power systems and Microgrid.