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The Design of A Distributed Rating Scheme for Peer-to-peer Systems

The Design of A Distributed Rating Scheme for Peer-to-peer Systems. Debojyoti Dutta 1 , Ashish Goel 2 , Ramesh Govindan 1 , Hui Zhang 1 1 University of Southern California 2 Stanford University. Outline. Research motivations Basic design issues in P2P rating schemes

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The Design of A Distributed Rating Scheme for Peer-to-peer Systems

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  1. The Design of A Distributed Rating Scheme for Peer-to-peer Systems Debojyoti Dutta1, Ashish Goel2, Ramesh Govindan1, Hui Zhang1 1University of Southern California 2Stanford University

  2. Outline • Research motivations • Basic design issues in P2P rating schemes • A distributed rating scheme to incentivize cooperation in P2P file-sharing systems • Dealing with collusion and malice • Conclusion & future work P2Pecon

  3. Research motivations • Object: P2P file-sharing systems • Open social communities. • An explicit reputation layer was ignored in the original design. • Goal: Build reputation in such systems • Incentive for user participation • free-riding phenomenon [Adar et al. 2000][Saroiu et al. 2001] • Isolation of malicious users • distribution of inauthentic files • propagation of virus or worms [VBS.Gnutella][Fizzer.Kazza] P2Pecon

  4. P2P rating: basic design issues • “Distributed” rating • following P2P design philosophy. • “Efficient” rating • low cost to run and maintain this reputation system. • “Collusion-proof” rating • Effectiveness. P2Pecon

  5. A distributed rating scheme • To incentivize cooperation in P2P file-sharing systems • Main components • Positive rating • Rating verification scheme P2Pecon

  6. Positive rating • The recognized service done to the community • Ri of user i: non-decreasing with the number of successful requests that it has satisfied within some sliding time window. • The higher Ri user i has, the better service it gets from the network. P2Pecon

  7. ? Verify if R’i is true for i Rating Ri (i, R’i) Data request User i User j Verification-based rating scheme P2Pecon

  8. lightweight L Two verification schemes • Structured verification scheme (SVS) • Each user has a set of designated supervisors which keep its up-to-date reputation information. • The supervisors are responsible for the verification. • Unstructured verification scheme (UVS) • A user j queries some of user i’s claimed customers for the verification, and believes i when the majority of the probed users reply with a “yes”. P2Pecon

  9. Assumption • Users are distinguished by their IP addresses. • At a given time, one IP address corresponds to an unique user. P2Pecon

  10. SVS – the supervising topology • In the supervisory directed graph • Any user is random to its supervisors. • No small supervising loop exists. • There is a fast reactive approach for any user j to deliver a message to any other user i’s supervisors, and the path never includes i. P2Pecon

  11. 0 0 256 224 32 256 Each user has a O(logN)-entry routing table and a O(logN)-successor list. All routing operations go clockwise 64 192 96 160 128 A Chord[stoica2001] supervising overlay Network user Supervising Pointer A Chord network with 8 users and 8-bit key space P2Pecon

  12. SVS – the supervising topology • In the supervisory directed graph • Any user is random to its supervisors. • No small supervising loop exists. • There is a fast reactive approach for any user j to deliver a message to any other user i’s supervisors, and the path never includes i. P2Pecon

  13. Yes/No user i’s supervisors Yes/No ID(i) verification request user i Supervising overlay Rating verification in SVS user j P2Pecon

  14. ? • “Efficient” rating • Extra cost to maintain a supervisory overlay when the underlying network is not DHT-based. • Repetitive actions when there are multiple supervisors. Structured verification scheme  • “Distributed” rating  • “Collusion-proof” rating P2Pecon

  15. Unstructured verification scheme • When user j decides to verify user i’s rating, it gets a portion of i’s customer list, and asks the users on the list if i did the claimed service to them. • When the majority of the probed users reply with a “yes”, j is convinced that R’i is Ri. • The customer samples should be random on the full customer list of node i. • Disclosure of full customer list could raise privacy concern, and incur high communication cost. P2Pecon

  16. hashing 2k-1 0 user i’s customer vector [ 2, 3, 1, 2] Randomly sampling without the complete customer list user i’s customer list P2Pecon

  17. selfish malicious altruistic non-colluding colluding P2P users users P2Pecon

  18. Colluding selfish users • Possible solution 1: discrete rating • Grade : if a user has served no more than 10 users. • Grade   : if a user has served between 10 and 100 users. • Grade    : if a user has served more than 1000 users. • Possible solution 2: rating as virtual currency • A user has to pay (reduce its rating) for the service it claims to have received. • SVS: asks the requestor’s supervisors for a payment. • LUVS: future work. P2Pecon

  19. Colluding malicious users • One possible strategy • A user i quickly earns a high rating by faking transactions with other colluding users. • User i then does bad things until earns bad-enough reputation. • User i quits the network to clear its history, • User i rejoins the network and repeats the above actions. P2Pecon

  20. Conclusion & future work • A simple distributed rating scheme to incentivize cooperation in P2P file-sharing systems. • Two distinct verification schemes • Refine LUVS scheme to handle colluding selfish users. • Refine our rating scheme to be collusion-proof. P2Pecon

  21. Backup slides P2Pecon

  22. 32 [2,4) [8,16) [1,2) [32,64) [4,8) [16,32) [128,256) [64,128) 64 96 160 224 128 192 Range 6 Range 7 Range 8 Range 2 Range 5 Range 4 Range 3 Range 1 Chord – routing table setup Network user Pointer 0 255 A Chord network with 8 users and 8-bit key space P2Pecon

  23. P2P users • Selfish vs. malicious • Selfish users: maximize the number of successful requests with good quality. • Malicious users: subvert the system. • Non-colluding vs. colluding • Non-colluding users: work individually. • colluding users: organize into a clique with some common interests. P2Pecon

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