A mechanism that provides incentives for truthful feedback in peer-to-peer systems
We propose a mechanism for providing the incentives for reporting truthful feedback in a peer-to-peer system for exchanging services (or content). This mechanism is to complement reputation mechanisms that employ ratings’ feedback on the various transactions in order to provide incentives to peers for offering better services to others. Under our approach, each of the transacting peers (rather than just the client) submits a rating on the performance of their mutual transaction. If these are in disagreement, then both transacting peers are punished, since such an occasion is a sign that one of them is lying. The severity of each peer’s punishment is determined by his corresponding non-credibility metric; this is maintained by the mechanism and evolves according to the peer’s record. When under punishment, a peer does not transact with others. We model the punishment effect of the mechanism in a peer-to-peer system as a Markov chain that is experimentally proved to be very accurate. According to this model, the credibility mechanism leads the peer-to-peer system to a desirable steady state isolating liars. Then, we define a procedure for the optimization of the punishment parameters of the mechanism for peer-to-peer systems of various characteristics. We experimentally prove that this optimization procedure is effective and necessary for the successful employment of the mechanism in real peer-to-peer systems. Then, the optimized credibility mechanism is combined with reputation-based policies to provide a complete solution for high performance and truthful rating in peer-to-peer systems. The combined mechanism was experimentally proved to deal very effectively with large fractions of collaborated liar peers that follow static or dynamic rational lying strategies in peer-to-peer systems with dynamically renewed population, while the efficiency loss induced to sincere peers by the presence of liars is diminished. Finally, we describe the potential implementation of the mechanism in real peer-to-peer systems.
KeywordsCredibility Rational adversaries Collusion Sybil attack Strategyproof Markov model Steady state
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- 1.Dellarocas, C. (2003). Efficiency through feedback-contingent fees and rewards in auction marketplaces with adverse selection and moral hazard. In Proc. of the 3rd ACM conference on electronic commerce, San Diego, CA, USA, June 2003. Google Scholar
- 4.Aberer, K., & Despotovic, Z. (2001). Managing trust in a peer-to-peer information system. In Proc. of the 10th international conference on information and knowledge management, New York, NY, USA, November 2001. Google Scholar
- 5.Kamvar, S. D., Schlosser, M. T., & Garcia-Molina, H. (2003). EigenRep: reputation management in peer-to-peer networks. In: Proc. of the twelfth international world wide web conference, Budapest, Hungary, May 2003. Google Scholar
- 6.Papaioannou, T. G., & Stamoulis, G. D. (2005). An incentives’ mechanism promoting truthful feedback in peer-to-peer systems. In Proc. of the 5th IEEE/ACM international symposium in cluster computing and the grid, Cardiff, UK, May 2005. Google Scholar
- 7.Papaioannou, T. G., & Stamoulis, G. D. (2005). Optimizing an incentives’ mechanism for truthful feedback in virtual communities. In Proc. of the 4th international conference on autonomous agents and multiagent systems, Utrecht, The Netherlands, July 2005. Google Scholar
- 8.Dellarocas, C. (2000). Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior. In Proc. of the 2nd ACM conference on electronic commerce, Minneapolis, MN, USA, October 2000. Google Scholar
- 10.Chen, M., & Singh, J. P. (2001). Computing and using reputations for internet ratings. In Proc. of the 3rd ACM conference on electronic commerce, New York, NY, USA, October 2001. Google Scholar
- 17.Feldman, M., Papadimitriou, C., Chuang, J., & Stoica, I. (2004). Free-riding and white-washing in peer-to-peer systems. In Proc. of the ACM SIGCOMM workshop on practice and theory of incentives in networked systems, Portland, Oregon, USA, September 2004. Google Scholar
- 18.Ngan, T.-W. J., Wallach, D. S., & Druschel, P. (2003). Enforcing fair sharing of peer-to-peer resources. In Proc. of the 2nd international workshop on peer-to-peer systems, Berkeley, CA, USA, February 2003. Google Scholar
- 20.Jurca, R., & Faltings, B. (2004). An incentive compatible reputation mechanism. In Proc. of IEEE conference on electronic commerce, Newport Beach, CA, USA, June 2004. Google Scholar
- 22.Jurca, R., & Faltings, B. (2004). Eliciting truthful feedback for binary reputation mechanisms. In Proc. of IEEE/WIC/ACM international conference on web intelligence, Beijing, China, September 2004. Google Scholar
- 23.Dewan, P., & Dasgupta, P. (2009). P2p reputation management using distributed identities and decentralized recommendation chains. IEEE Transactions on Knowledge and Data Engineering, 99(1). Google Scholar
- 26.Jøsang, A., Hird, S., & Faccer, E. (2003). Simulating the effect of reputation systems on e-markets. In Proc. of the 1st international conference on trust management, Crete, Greece, May 2003. Google Scholar
- 27.Antoniadis, P., Courcoubetis, C., Mason, R., Papaioannou, T. G., Stamoulis, G. D., & Weber, R. Results of peer-to-peer market models, September 2004. Project IST MMAPPS: Deliverable 8. Available at: http://www.mmapps.info.
- 28.Pretty good privacy. http://www.pgp.com/.