Advances in Multimedia

Advances in Multimedia / 2007 / Article
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Toward the Next-Generation Peer-to-Peer Services

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Research Article | Open Access

Volume 2007 |Article ID 092485 | https://doi.org/10.1155/2007/92485

Gayatri Swamynathan, Ben Y. Zhao, Kevin C. Almeroth, Haitao Zheng, "Globally Decoupled Reputations for Large Distributed Networks", Advances in Multimedia, vol. 2007, Article ID 092485, 14 pages, 2007. https://doi.org/10.1155/2007/92485

Globally Decoupled Reputations for Large Distributed Networks

Academic Editor: Shigang Chen
Received08 Mar 2007
Accepted07 Jun 2007
Published12 Jul 2007

Abstract

Reputation systems help establish social control in peer-to-peer networks. To be truly effective, however, a reputation system should counter attacks that compromise the reliability of user ratings. Existing reputation approaches either average a peer's lifetime ratings or account for rating credibility by weighing each piece of feedback by the reputation of its source. While these systems improve cooperation in a P2P network, they are extremely vulnerable to unfair ratings attacks. In this paper, we recommend that reputation systems decouple a peer's service provider reputation from its service recommender reputation, thereby, making reputations more resistant to tampering. We propose a scalable approach to system-wide decoupled service and feedback reputations and demonstrate the effectiveness of our model against previous nondecoupled reputation approaches. Our results indicate that decoupled approache significantly improves reputation accuracy, resulting in more successful transactions. Furthermore, we demonstrate the effectiveness and scalability of our decoupled approach as compared to PeerTrust, an alternative mechanism proposed for decoupled reputations. Our results are compiled from comprehensive logs collected from Maze, a large file-sharing system with over 1.4 million users supporting searches on 226TB of data.

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Copyright © 2007 Gayatri Swamynathan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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