AI-Driven Cyber Risk Management Framework

As technological advancements continue to shape smart cities, the complex and interconnected digital networks within these infrastructures are increasingly susceptible to cyber threats. This PhD thesis explores the application of Artificial Intelligence (AI) as a powerful tool for managing and mitigating cyber risks in these advanced infrastructures and network systems. We focus on developing a proactive approach that combine the early detection, comprehensive assessment, and effective mitigation of impending cyber threats. To achieve this goal, we propose an AI-based framework that harnesses the power of Machine Learning (ML), Reinforcement Learning (RL), Natural Language Processing (NLP), and Graph Theory. By employing these techniques, our framework aims to fortify network and system resilience, providing robust cyber risk management by artificial intelligence and for smart cities. This work paves the way for innovative risk management strategies that not only react to cyber threats but also anticipate and neutralize them effectively.