Peer-to-peer (P2P) platforms are gaining increasing popularity due to their scalability, robustness and self-organization. In P2P systems, peers interact directly with each other to share resources or exchange services without a central authority to manage the interaction. However, these features expose P2P platforms to malicious attacks that reduce the level of trust between peers and in extreme situations, may cause the entire system to shut down. Therefore, it is essential to employ a trust management system that establishes trust relationships among peers. Current P2P trust management systems use binary categorization to classify peers as trustworthy or not trustworthy. However, in the real world, trustworthiness is a vague concept; peers have different levels of trustworthiness that affect their overall trust value. Therefore, in this paper, we developed a novel trust management algorithm for P2P platforms based on Hadith science where Hadiths are systematically classified into multiple levels of trustworthiness, based on the quality of narrator and content. To benchmark our proposed system, HadithTrust, we used two state-of-art trust management systems, EigenTrust and InterTrust, with no-trust algorithm as a baseline scenario. Various experimental results demonstrated the superiority of HadithTrust considering eight performance measures.
An SETM Algorithm for Combating SSDF Attack in Cognitive Radio Networks
