Qiao Lian, Zheng Zhang, Mao Yang, Ben Y. Zhao, Yafei Dai, and Xiaoming Li
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.
|Publisher||IEEE Computer Society|
Copyright © 2007 IEEE. Reprinted from IEEE Computer Society. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to email@example.com. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.