Peer cluster: a maximum flow-based trust mechanism in P2P file sharing networks

Trust mechanism has become a research focus in recent years as a novel and valid way to ensure the transaction security in peer-to-peer file sharing networks. Nevertheless, some fundamental challenges still exist, for example: How can malicious peers be effectively isolated? How can various threats of manipulation by strategic peers be resisted? What strategy should be used to ensure that the service providers are authentic peers? Considering these challenges in our minds, in this paper, we propose a new trust mechanism based on the maximum flow theory. We firstly add a few prestigious peers into a cluster as the original members according to their transaction behaviors in a period; then, we perform maximum flow algorithm and identify those peers that still link from (to) the peers in the cluster as new members, which is carried out repeatedly, and almost every normal peer would finally become the member of the cluster. Each request peer has the priority to select downloading sources from this cluster according to our trust mechanism. In this way, the malicious peers are isolated, and their transaction behaviors are also confined largely even though they have high reputation. Extensive experimental results confirm the efficiency of our trust mechanism against the threats of exaggeration, cheat, collusion, and disguise. Copyright © 2013 John Wiley & Sons, Ltd.

[1]  Robert Sedgewick,et al.  Algorithms in c, part 5: graph algorithms, third edition , 2001 .

[2]  Paul Resnick,et al.  Reputation systems , 2000, CACM.

[3]  Chrysanthos Dellarocas,et al.  Sanctioning Reputation Mechanisms in Online Trading Environments with Moral Hazard , 2004 .

[4]  Audun Jøsang,et al.  A survey of trust and reputation systems for online service provision , 2007, Decis. Support Syst..

[5]  Ian T. Foster,et al.  Mapping the Gnutella Network: Macroscopic Properties of Large-Scale Peer-to-Peer Systems , 2002, IPTPS.

[6]  Félix Gómez Mármol,et al.  Security threats scenarios in trust and reputation models for distributed systems , 2009, Comput. Secur..

[7]  Yuguang Fang,et al.  A Fine-Grained Reputation System for Reliable Service Selection in Peer-to-Peer Networks , 2007, IEEE Transactions on Parallel and Distributed Systems.

[8]  Philip Robinson,et al.  PathTrust: A Trust-Based Reputation Service for Virtual Organization Formation , 2006, iTrust.

[9]  Mark Handley,et al.  A scalable content-addressable network , 2001, SIGCOMM '01.

[10]  Tharam S. Dillon,et al.  Fuzzy trust evaluation and credibility development in multi-agent systems , 2007, Appl. Soft Comput..

[11]  D. R. Fulkerson,et al.  Maximal Flow Through a Network , 1956 .

[12]  Andrew V. Goldberg,et al.  A new approach to the maximum flow problem , 1986, STOC '86.

[13]  S. Buchegger,et al.  A Robust Reputation System for P2P and Mobile Ad-hoc Networks , 2004 .

[14]  Ford-Fulkerson Max Flow Labeling Algorithm , 1998 .

[15]  Shanshan Song,et al.  Trusted P2P transactions with fuzzy reputation aggregation , 2005, IEEE Internet Computing.

[16]  Ayman I. Kayssi,et al.  PATROL-F - A Comprehensive Reputation-Based Trust Model with Fuzzy Subsystems , 2006, ATC.

[17]  Audun Jøsang,et al.  A Logic for Uncertain Probabilities , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[18]  David Hales,et al.  Emergent Social Rationality in a Peer-to-Peer System , 2008, Adv. Complex Syst..

[19]  C. Castelfranchi,et al.  Social Trust : A Cognitive Approach , 2000 .

[20]  Audun Jøsang,et al.  AIS Electronic Library (AISeL) , 2017 .

[21]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[22]  Ion Stoica,et al.  Robust incentive techniques for peer-to-peer networks , 2004, EC '04.

[23]  Antony I. T. Rowstron,et al.  Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems , 2001, Middleware.

[24]  Karl Aberer,et al.  P-Grid: A Self-Organizing Access Structure for P2P Information Systems , 2001, CoopIS.

[25]  George C. Polyzos,et al.  Stimulating Participation in Wireless Community Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[26]  Akihiro Nakao,et al.  On cooperative and efficient overlay network evolution based on a group selection pattern , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[27]  Ling Liu,et al.  PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities , 2004, IEEE Transactions on Knowledge and Data Engineering.

[28]  Chrysanthos Dellarocas Efficiency and Robustness of Binary Feedback Mechanisms in Trading Environments with Moral Hazard , 2003 .

[29]  Rino Falcone,et al.  Integrating Trustfulness and Decision Using Fuzzy Cognitive Maps , 2003, iTrust.

[30]  Hector Garcia-Molina,et al.  The Eigentrust algorithm for reputation management in P2P networks , 2003, WWW '03.

[31]  Yao-Hua Tan,et al.  Trust and Deception in Virtual Societies , 2001, Springer Netherlands.

[32]  Yong Wang,et al.  Bayesian Network Based Trust Management , 2006, ATC.

[33]  Stefan Schmid,et al.  On the topologies formed by selfish peers , 2006, PODC '06.

[34]  Bruce Edmonds,et al.  Towards the evolution of social structure , 2009, Comput. Math. Organ. Theory.

[35]  Yufeng Wang,et al.  Poisonedwater: An improved approach for accurate reputation ranking in P2P networks , 2010, Future Gener. Comput. Syst..

[36]  David C. Parkes,et al.  The price of selfish behavior in bilateral network formation , 2005, PODC '05.

[37]  Aruna Seneviratne,et al.  Cost-effective broadcast for fully decentralized peer-to-peer networks , 2003, Comput. Commun..

[38]  Bui Minh Nhat Searching in P2P Networks: A Survey , 2009 .