On exploring generative AI for privacy preservation in IoT ecosystems
Hafssa Benaboud, Hiba Kandil, Saiida Lazaar · 2025
The Internet of Things (IoT) generates vast amounts of sensitive data, raising significant privacy concerns that demand innovative solutions. Generative AI (GAI) has emerged as a promising approach to address these challenges, offering capabilities such as data anonymization, synthetic data generation, and secure data-sharing mechanisms. This chapter explores the privacy issues inherent to IoT environments, examines GAI-driven approaches for privacy preservation, and highlights applications across various IoT domains, including smart homes, smart cities, healthcare, and industrial IoT. Furthermore, the chapter delves into critical challenges and ethical considerations associated with GAI, such as adversarial attacks, bias mitigation, and the balance between privacy and data utility.