An Empirical Study of Collusion Behavior in the Maze P2P File-Sharing System

Qiao Lian, Zheng Zhang, Mao Yang, Ben Y. Zhao, Yafei Dai, and Xiaoming Li

Abstract

Peer-to-peer networks often use incentive policies to encourage cooperation between nodes. Such systems are generally susceptible to collusion by groups of users in order to gain unfair advantages over others. While techniques have been proposed to combat web spam collusion, there are few measurements of real collusion in deployed systems. In this paper, we report analysis and measurement results of user collusion in Maze, a large-scale peer-to-peer file sharing system with a non-net-zero point-based incentive policy. We search for colluding behavior by examining complete user logs, and incrementally refine a set of collusion detectors to identify common collusion patterns.We find collusion patterns similar to those found in web spamming. We evaluate how proposed reputation systems would perform on the Maze system. Our results can help guide the design of more robust incentive schemes.

Details

Publication typeInproceedings
URLhttp://www.computer.org/portal/site/ieeecs/index.jsp
Pages13
NumberMSR-TR-2006-14
InstitutionMicrosoft Research
PublisherIEEE Computer Society
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