Blockchain and AI-based methods for trust management in IoT: A comprehensive survey

Abstract

The rapid expansion of the Internet of Things (IoT) is driving the integration of billions of connected devices across various domains, including healthcare, transportation, and smart urban systems. Although this proliferation offers considerable advantages in terms of functionality and operational efficiency, it also brings to the forefront a range of pressing concerns, particularly in relation to security, reliability, and privacy. These challenges are largely rooted in the decentralized and dynamic architecture of IoT ecosystems. In this context, trust and reputation mechanisms have become increasingly vital for enabling secure and reliable interactions between devices and users. This paper examines recent advances in trust management models tailored to IoT environments, with a focus on approaches leveraging blockchain technologies, machine learning techniques, and edge or fog computing paradigms. We assess the practical implications of these solutions, discussing both their strengths and inherent limitations. Furthermore, we identify key open issues such as scalability, data protection, and interoperability across platforms, and we outline potential research directions to support the development of more robust and adaptable trust frameworks for the evolving IoT landscape.