PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities

TLDR

Peer‑to‑peer online communities offer both opportunities and threats, and community‑based reputations can mitigate these threats by estimating peer trustworthiness. The authors introduce PeerTrust, a reputation‑based trust framework designed to quantify and compare peer trustworthiness in P2P networks. PeerTrust employs an adaptive trust model that combines feedback, transaction volume, feedback credibility, transaction and community context factors into a general trust metric, and implements this model in a decentralized structured P2P environment. Experiments and evaluation mechanisms demonstrate the feasibility and benefits of PeerTrust, validating its effectiveness and cost‑efficiency.

Abstract

Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such communities is to use community-based reputations to help estimate the trustworthiness of peers. We present PeerTrust - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network. PeerTrust model has two main features. First, we introduce three basic trust parameters and two adaptive factors in computing trustworthiness of peers, namely, feedback a peer receives from other peers, the total number of transactions a peer performs, the credibility of the feedback sources, transaction context factor, and the community context factor. Second, we define a general trust metric to combine these parameters. Other contributions of the paper include strategies used for implementing the trust model in a decentralized P2P environment, evaluation mechanisms to validate the effectiveness and cost of PeerTrust model, and a set of experiments that show the feasibility and benefit of our approach.