Smart City Security

The global rise of smart cities, driven by pervasive sensing technologies and advanced Information and Communication Technology (ICT) infrastructure, promises significant improvements in urban sustainability and service delivery. However, the complex and heterogeneous nature of smart city networks introduces critical security vulnerabilities, particularly since energy-efficient device designs often overlook robust protection measures. This makes such environments increasingly susceptible to cyber threats, including phishing, malware, and denial-of-service attacks, jeopardizing essential services and exposing sensitive data. Traditional security mechanisms are inadequate for addressing the scale and complexity of these threats. In this context, Artificial Intelligence (AI) and Machine Learning (ML) offer transformative solutions. By enabling real-time data analysis, automated threat detection, and intelligent decision-making, AI/ML technologies empower proactive security through advanced techniques such as anomaly detection, malware classification, and intrusion detection using models like Deep Reinforcement Learning and Generative Adversarial Networks (GANs). Furthermore, the integration of AI/ML with blockchain enhances the trust, integrity, and resilience of cyber-physical systems against manipulation and data breaches. This chapter explores the strategic role of AI and ML in fortifying smart city infrastructures, presenting a path toward secure, adaptive, and resilient urban ecosystems.