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A reputation-based trust management in peer-to-peer network systems

A reputation-based trust management in peer-to-peer network systems

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A reputation-based trust management in peer-to-peer network systems

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  1. A reputation-based trust management in peer-to-peer network systems Natalia Stakhanova, Sergio Ferrero, Johnny Wong, Ying Cai Department of Computer Science Iowa State University Ames, Iowa, USA

  2. Outline • Peer-to-peer(P2P) networks overview • Related work • Proposed approach • Experiments

  3. Peer-to-peer (P2P)networks overview • P2P network - an overlay network of peers exchanging resources • common uses: file sharing, distributed computing, instant messaging • types: • Centralized (Napster) • Central indexing server contains information about all peer’s shared files • Decentralized (Gnutella, Freenet) • No central indexing, all peers are equal • Very popular • Hybrid (KaZaA, FastTrack) • Supernodes maintain index of files shared by their local peers

  4. P2P networks overview • Differences with traditional networks • Highly dynamic • autonomous peers • peers leave & join the network at any time • shared storage • Peers act as servers and clients

  5. P2P security threats • Denial-Of-Service attacks (DoS) • Decentralized P2P networks (Gnutella) • Virus distribution • Dishonest upload • Unauthorized access to information Goal: communication with trusted peers only

  6. Reputation-based approach • Natural mechanism for selecting trusted partners for communication • limit communication with unreliable peers • Most commonly used

  7. Related work • Centralized approaches • Debit-Credit Reputation Computation (DCRC) schema • Each peer tracks its own positive contribution using credit-debit mechanism • Reputation Computation Agent (RCA) periodically collects reputations • Decentralized approaches • NICE • Reputation is in form of cookies which express peer’s satisfaction about the transactions • If no cookie is found information is requested from • P2PRep • Reputation of the peer is based on other peer’s opinion • Request peer’s opinion on one’s reputation through polling protocol • Others • Daswani and Garcia-Molina’s schema for allocating resources fairly • Traffic management based on load-balancing policies • DoS attacks only

  8. Factors to be considered inreputation-based approach • Extensive traffic in Gnutella-like P2P network • Storage • central • local • Cooperation of other peers • System overhead

  9. Proposed approach • Reputation calculation is based the monitored activity of the connected peers • assessing the reputation of the peers before accepting traffic from other peers • if traffic is accepted update reputation of peers involved • Decentralized - reputations are stored and managed locally

  10. Contribution of our approach • Fully decentralized model • Requires no cooperation for reputation computation • On demand calculations • Lightweight – little system overhead

  11. Reputation calculation • Peer’s reputation indicates its contribution to the functioning of the P2P network • Four factors determining reputation: • Resource search • Resource upload • Resource download • Traffic extensiveness • Factors = actions • Bad actions • Good actions

  12. Resource search • willingness of a peer to forward traffic employ “trailer” as an addition to Query message • each peer that forwards the query adds its ID to the “trailer” • when peer forms QueryHit, it transfers a “trailer” from Query to QueryHit • peer originated a query receives QueryHit with “trailer” and updates reputations

  13. Resource upload • Indicates another peer’s interest in the shared resource • Completely uploaded file is a successful upload or good action

  14. Resource download • reflects the quality of the downloaded information • User decides if download was successful

  15. Traffic extensiveness • help to evaluate the traffic load coming from all connected peers • based on the average load • load is extensive if it exceeds the average amount by a user pre-defined threshold LcK- current load from peer k t - threshold n - number of connected peers lj - number of bytes sent by peer j n LcK > ∑ lj /n * t j=1

  16. Reputation calculation • Reputation value (trust score) isa percent of bad actions happened during a period of time Ri = BAi/ TAi Ri - trust score of peer i TAi - total number of considered actions for this peer i BAi - number of bad actions for this peer i

  17. Trust thresholds • indicate peer’s trust policy • percent of bad actions acceptable by the peer

  18. The correspondence between trust thresholds and trust score Example: • trust score falls in range of “average” -> x1–(Ri–x2) Computations: 30-(13-4) = 21 21% of peer’s traffic is accepted within period k. Given: Ri=13 x1=30 x2=4

  19. P2P client … Security Manager Reputation Manager Reputation repository Internet Connection Engine Experiments: system design • implementation were based on Phex version 0.9.5.54, a java-based Gnutella client

  20. Experimental setup • Network : 3 P2P clients set up as Ultrapeers • peer capacity - 20 queries per time period k • k=5 sec • Extensive traffic threshold t=1.7 • Trust thresholds • x1=20 • x2=5 • Initial reputation values for peers were set up manually

  21. Scenario 1 • Decrease of full reputation when peer P1 starts “acting” maliciously

  22. Scenario 2 • Reputation gain when peer starts “acting” properly

  23. Conclusion • We have proposed reputation-based trust management model for P2P networks • approach is decentralized • requires no peers’ cooperation • employs only on-demand calculations

  24. Future work • Enhancement of the model through • user profiling techniques • anomaly detection