GossipTrust for Fast Reputation Aggregation in Peer-to-Peer Networks

Abstract-- In peer-to-peer (P2P) networks, reputation aggregation and peer ranking are the most time-consuming and spacedemanding operations. This paper proposes a gossip-based reputation system (GossipTrust) for fast aggregation of global reputation scores. It leverages a Bloom filter based scheme for efficient score ranking. GossipTrust does not require any secure hashing or fast lookup mechanism, thus is applicable to both unstructured and structured P2P networks. Randomized gossiping with effective use of power nodes enables fast aggregation and fast dissemination of global scores in O(log2 n) time steps, where n is the network size. The gossip-based protocol is designed to tolerate dynamic peer joining and departure, as well as to avoid possible peer collusions. The scheme has a considerably low gossiping message overhead, i.e. O(nlog2 n) messages for n nodes. Bloom filters reduce the memory overhead per node to 512 KB for a 10,000-node network. We evaluate the performance of Goss...

• Type: Journal
• Year: 2008
• Where: TKDE
• Authors: Runfang Zhou, Kai Hwang, Min Cai
• Keywords: Filter Based Scheme, Global Reputation Scores, Reputation Aggregation, TKDE 2008