Bayesian memory-based reputation system

ABSTRACT

Reputation System provides a way to maintain trust through social control by utilizing feedbacks about the service providers' past behaviors. Conventional Memory-based Reputation System (MRS) is one of the most successful mechanisms in terms of accuracy. Though MRS performs well on giving predicted values for service providers offering averaging quality services, our experiments show that MRS performs poor on giving predicted values for service providers offering high and low quality services. We propose a Bayesian Memory-based Reputation System (BMRS) which uses Bayesian Theory to analyze the probability distribution of the predicted valued given by MRS and makes suitable adjustment. The simulation results, which are based on EachMovie dataset, show that our proposed BMRS has higher accuracy than MRS on giving predicted values for service providers offering high and low quality services.

REFERENCES

• 1: Andrews P. Reputation management: Building trust among virtual strangers. IBM Global Business Services. Sept. 2006.
• 2: Yu K, Schwaighofer A, Tresp V, et al. Probabilistic memory-based collaborative filtering[J].IEEE Transaction on Knowledge and Data Engineering, 2004, 16(1):56--69.
• 3: Andrews P, "Reputation management: Building trust among virtual strangers", IBM Global Business Services, Sept. 2006.
• 4: A. Abdul-Rahman and S. Hailes, "Supporting trust in virtual communities", Proc of the 33rd Hawaii International Conference on Systems Science, 2000.
• 5: Cahill, V. and Gray, E. et al, "Using trust for secure collaboration in uncertain environments", IEEE Pervasive Computing, 2/3. pp. 52--61.
• 6: Carbone, M., Nielsen, M. and Sassone, V., "A formal model for trust in dynamic networks", In Proceedings of Int. Conference on Software Engineering and Formal Methods, SEFM 2003., pp. 54--61.
• 7: Manchala D W, "Trust metrics, models and protocols for electronic commerce transactions", In Proceedings of 18th International Conference on Distributed Computing Systems. Amsterdam:IEEE Computer Society, 1998. 312--321.
• 8: Sepandar D. K., Mario T. S. and Hector G. M., "The EigenTrust algorithm for reputation management in P2P networks", In Proceedings of the 12th Int'l Conf. on World Wide Web. ACM Press, 2003. 640--651.
• 9: R. Levien, Attack Resistant Trust Metrics. PhD thesis, University of California at Berkeley.
• 10: C. N. Ziegler and G. Lausen, "Spreading activation models for trust propagation", In Proceedings of IEEE. International Conference on e-Technology, e-Commerce, and e-Service (EEE '04), 2004.
• 11: A. Jøsang, R. Ismail and C. Boyd, "A survey of trust and reputation systems for online service provision", Decision Support Systems, Volume 43, Issue 2 (March 2007), Pages: 618--644.
• 12: S. Song, K. Hwang, R. Zhou, and YK Kwok, "Trusted P2P Transactions with Fuzzy Reputation Aggregation," Internet Computing, IEEE, Vol. 9, No. 6. (2005), pp. 24--34.
• 13: P. Resnick and R. Zeckhauser, "Trust among strangers in internet transactions: empirical analysis of eBay's reputation system", The Economics of the Internet and E-Commerce, 2002.
• 14: A. Jøsang and J. Haller, "Dirichlet Reputation Systems" (to appear). Proceedings of the Second International Conference on Availability, Reliability and Security (ARES 2007), Vienna, April 2007
• 15: A. Jøsang and R. Ismail, "The Beta Reputation System". Proceedings of the 15th Bled Conference on Electronic Commerce, Bled, Slovenia, 17--19 June 2002.
• 16: Mui, L., Mohtashemi, M., Halberstadt, A., "A computational model of trust and reputation", In Proceedings of 35th Hawaii International Conference on System Science. (2002) 280--287
• 17: Withby A, Jøsang A and Indulska J., "Filtering Out Unfair Ratings in Bayesian Reputation Systems", Journal of Management Research, 2005, 4(2):48--64.
• 18: Jøsang A., Pope S., "Semantic constraints for trust transitivity", In:Proceedings of the 2nd Asia-Pacific Conference on Conceptual Modelling(APCCM2005), 59--68
• 19: Yu B. and Munindar P., "An evidential model of distributed reputation management". In proceeding of AAMAS02. 2002-07: 15--19
• 20: Brin S., Page L. Motwami R. and Winograd T., "The PageRank Citation Ranking: Bringing Order to The Web", Technical Report. Standford Digital Library Technologies Project. Stanford: Stanford University, CA, 1998
• 21: Xiong L, Liu L. PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities. IEEE transactions on knowledge and data engineering, 2004, 16 (7)

INDEX TERMS

Keywords:
Bayesian theory, memory-based, reputation system