Improving Peer-to-Peer Networks “Limited Reputation Sharing in P2P Systems” “Robust Incentive Techniques for P2P Networks”

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    17-Dec-2015

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<ul><li> Slide 1 </li> <li> Improving Peer-to-Peer Networks Limited Reputation Sharing in P2P Systems Robust Incentive Techniques for P2P Networks </li> <li> Slide 2 </li> <li> In this talk Peer-to-Peer Networks Properties / Challenges Threats Solutions </li> <li> Slide 3 </li> <li> Peer-to-Peer Networks Large Populations High Turnover Asymmetry of interest Zero-cost identity </li> <li> Slide 4 </li> <li> Peer-to-Peer Networks (2) Threats Malicious users: share bad resources Free-Riders: selfish users Solutions Limited Reputation Sharing in P2P Systems by Sergio Marti and Hector Garcia-Molina Robust Incentive Techniques for Peer-to-Peer Networks by M. Feldman, K. Lai, I. Stoica and J. Chuang </li> <li> Slide 5 </li> <li> Limited Reputation Sharing in P2P Systems by Sergio Marti and Hector Garcia-Molina Studies the performance of P2P resource-sharing network in the presence of malicious nodes Uses limited information sharing between peers Studies the effect of reputation systems </li> <li> Slide 6 </li> <li> System Model When a peer desires a file: Queries all or a subset of the peers for the file Collects responses (response set) Selects a provider and accesses the resource Verifies the authenticity of the file: V(R) If V(R) determines that the file is invalid, the peer fetches another file from the response set Peer wants to minimize the use of V(R) Limited Reputation Sharing in P2P Systems </li> <li> Slide 7 </li> <li> Threat Model: Malicious peers Propagate fake files Can pass false information Three types of malicious nodes: N: Do not misinform L: Lie about everyone C: Collude and give bad ratings to good nodes and good ratings to bad nodes Subversion Set: the set of unique fake files B : Percentage of malicious peers p B : Probability of a file to be in the Subversion set Limited Reputation Sharing in P2P Systems </li> <li> Slide 8 </li> <li> Reputation Systems Peers collect statistics about other peers and form opinions about them (reputation rating) 0 </li></ul>

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