Comprehensive Evaluations of Machine Learning enabled Trust and Reputation Models in Internet of Things

The Internet of Things (IoT) stands out as a pervasive technology, exerting a profound influence on various facets of our lives including social, commercial, and economic dimensions. IoT technologies hold immense potential for elevating human life. Despite these transformative benefits, the prevalence of cyber-attacks and threats poses considerable challenges to the security of IoT applications. Conventional standalone security measure (cryptography) have proven inadequate in heterogeneous and resource constraint IoT networks. To effectively tackle these challenges, machine learning (ML) techniques are applied in trust management for IoT security. This paper provides a comprehensive analysis of support vector machine (SVM) based models employed for trust management, to address challenges associated with trust evaluation in IoT. Furthermore, we examine existing research to demonstrate the effectiveness and applicability of ML in IoT trust management. The paper concludes with future research directions and potential advancements in this field.