On Distributed Rating Systems for Peer-to-Peer Networks

In recent years, many distributed rating systems have been proposed against the increasing misbehaviors of peers in peer-to-peer (P2P) networks. However, the low accuracy, long-response time and vulnerabilities under the adversary attacks of P2P rating systems have long been criticized and hindering the practical deployment of such a mechanism. There is also a lack of systematic analysis and evaluation for understanding the systems. In this paper, we first present a framework of stochastic analytical model for evaluating P2P rating systems. The performances of two representative designs, namely the unstructured self-managing rating (UMR) system and the structured supervising rating (SSR) system, are then studied with our model. We identify the positive features as well as the negative ones of the two designs with different design choices and under various network environments and adversary attacks. We also propose a configurable loosely supervising rating system, and show that this system works inexpensively, and could make trade-off between the false rating attack resistance of the UMR system and the accuracy, responsiveness, whitewashing attack resistance as well as a failure resilience of the SSR system, thus providing a better overall performance according to the application context.