Trusted P2P transactions with fuzzy reputation aggregation

By Shanshan Song, Kai W. Hwang, Runfang Zhou, Yu-Kwong Kwok. IEEE Internet Computing, 2005

436 citations recorded by the source corpus.

Internet commerce and online commodity exchanges suffer from distrust among sellers and buyers, who are often strangers to each other. The authors present a new P2P reputation system based on fuzzy logic inferences, which can better handle uncertainty, fuzziness, and incomplete information in peer trust reports. This system aggregates peer reputations with affordable message overhead. By testing the system using eBay transaction data in the public domain, the authors seek to demonstrate the efficacy and robustness of two P2P reputation systems - fuzzytrust and eigentrust - at establishing trust among the peers in P2P applications.

View Paper: https://www.semanticscholar.org/paper/049ba6d4a96b74c3508648654956350724d27221

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Kevin J. Hoffman
2. David Zage
3. Cristina Nita-Rotaru
4. Runfang Zhou
5. R. Ureña

Citations in the corpus

• PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing (2007, background): “Identifying trustworthy peers is especially necessary in commercial P2P applications, such as P2P auctions [18], trusted content delivery [23], pay-per-transaction [29], and P2P service discovery [20].”
• A survey of attack and defense techniques for reputation systems (2009, methodology): “Other proposals include the use of Bayesian procedures [Aringhieri et al. 2006; Buchegger and Le Boudec 2004] or fuzzy decision logic [Song et al. 2005] to transform the user feedback into ratio-scaled variables.”