AI-enabled Trust in Distributed Networks

Cybersecurity, as a crucial aspect of the information society, requires significant attention. Fortunately, concept trust, rooted in sociology, has been studied order to enhance cybersecurity by evaluating trustworthiness nodes with artificial intelligence (AI) techniques distributed networks (DNs). However, scalability issues faced AI-enabled trust hinder its integration DNs. Currently, there is lack comprehensive review article that explores current state development applications. This paper aims address this gap providing state-of-the-art focuses on and how it can be facilitated through AI, particularly utilizing machine learning deep methods. Additionally, provides comparison analysis three key domains field trust: management (TM), intrusion detection systems (IDS), recommender (RS). Some open problems challenges currently exist are manifested, some suggestions for future work presented.