Fighting Pollution Attack in Peer-to-Peer Streaming Systems: A Dynamic Reputation Management Approach

Abstract

P2P streaming systems are popular applications on internet. However, due to the open nature, P2P streaming systems are vulnerable to malicious attacks, especially data pollution attacks. Reputation-based mechanisms are most effective mechanisms to defend data pollution attacks in P2P streaming systems. In this paper, we propose a dynamic reputation management. In our proposed mechanism, a peer's reputation consists of direct and indirect trust. The confidence factor is used to determine the weight of direct trust. We introduce Gompertz Function to adjust the confidence factor, the more interactions, the larger weight of direct trust value is. Besides, to lower the complexity of calculating indirect trust, we introduce threedegree of separation, which only includes neighbors within three degrees while calculating indirect trust. Simulation results show that our proposed reputation management scheme can effectively separate malicious peers, reduce the dissemination of polluted data chunks and defend various kinds of data pollution attacks.