Abstract
<jats:p>This chapter presents a comprehensive analysis of methods for securing IoT networks in smart cities, addressing the technical, operational, and regulatory challenges unique to these environments. It begins by exploring the foundational role of IoT in enhancing urban efficiency, connectivity, and sustainability. Security threats, including device vulnerabilities, unauthorized access, and privacy breaches, are examined, highlighting the limitations of traditional models. Advanced solutions such as cryptographic techniques, secure connectivity, and distributed authentication are discussed. Privacy-preserving data processing approaches like differential privacy, federated learning, and secure multi-party computation are explored, ensuring a balance between data protection and system performance. The chapter also emphasizes the significance of AI and ML in threat detection, anomaly analysis, and proactive response. Edge and fog computing are highlighted for their potential in reducing latency and enhancing data privacy.</jats:p>