A Robust Reputation System for P2P and Mobile Ad-hoc Networks

TLDR

Reputation systems are vulnerable to false ratings, and relying solely on direct observations fails to exploit all available information. The authors propose a fully distributed reputation system that resists false information dissemination. The system maintains per‑node reputation and trust ratings, exchanges first‑hand data, and applies a modified Bayesian filter to accept only compatible second‑hand information, updating ratings and trust while keeping all data distributed. The approach enables users to redeem reputations and prevents exploitation by incorporating re‑evaluation and fading of reputation scores.

Abstract

Reputation systems can be tricked by the spread of false reputation ratings, be it false accusations or false praise. Simple solutions such as exclusively relying on one’s own direct observations have drawbacks, as they do not make use of all the information available. We propose a fully distributed reputation system that can cope with false disseminated information. In our approach, everyone maintains a reputation rating and a trust rating about everyone else that they care about. From time to time first-hand reputation information is exchanged with others; using a modified Bayesian approach we designed and present in this paper, only second-hand reputation information that is not incompatible with the current reputation rating is accepted. Thus, reputation ratings are slightly modified by accepted information. Trust ratings are updated based on the compatibility of second-hand reputation information with prior reputation ratings. Data is entirely distributed: someone’s reputation and trust is the collection of ratings maintained by others. We enable redemption and prevent the sudden exploitation of good reputation built over time by introducing re-evaluation and reputation fading.