Skip to main content
SpringerLink
Log in

A Comprehensive and Adaptive Trust Model for Large-Scale P2P Networks

  • Regular Paper
  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

Based on human psychological cognitive behavior, a Comprehensive and Adaptive Trust (CAT) model for large-scale P2P networks is proposed. Firstly, an adaptive trusted decision-making method based on HEW (Historical Evidences Window) is proposed, which can not only reduce the risk and improve system efficiency, but also solve the trust forecasting problem when the direct evidences are insufficient. Then, direct trust computing method based on IOWA (Induced Ordered Weighted Averaging) operator and feedback trust converging mechanism based on DTT (Direct Trust Tree) are set up, which makes the model have a better scalability than previous studies. At the same time, two new parameters, confidence factor and feedback factor, are introduced to assign the weights to direct trust and feedback trust adaptively, which overcomes the shortage of traditional method, in which the weights are assigned by subjective ways. Simulation results show that, compared to the existing approaches, the proposed model has remarkable enhancements in the accuracy of trust decision-making and has a better dynamic adaptation capability in handling various dynamic behaviors of peers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Chang E, Thomson P, Dillon T et al. The fuzzy and dynamic nature of trust. In Proc. the 2nd International Conference on Trust, Privacy and Security in Digital Business (Trustbus'05) in conjunction with DEXA, Copenhagen, Denmark, August 22–26, 2005, pp.161–174.

  2. Li X Y, Gui X L. Research on dynamic trust model in large-scale distributed environment. Journal of Software, 2007, 18(6): 1510–1521.

    Article  Google Scholar 

  3. Li H Z, Singhal M. Trust management in distributed systems. IEEE Computer, 2007, 40(2): 45–53.

    Google Scholar 

  4. Ji M, Orgun M A. Trust management and trust theory revision. IEEE Transactions on Systems, Man and Cybernetics, 2006, 36(3): 451–460.

    Article  Google Scholar 

  5. Sloman M. Trust-management in Internet and pervasive systems. IEEE Intelligent Systems, 2004, 19(5): 77–79.

    Google Scholar 

  6. Xiong L, Liu L. Peer-Trust: Supporting reputation-based trust in peer-to-peer communities. IEEE Transactions on Data and Knowledge Engineering, 2004, 16(7): 843–857.

    Article  Google Scholar 

  7. Liang Z Q, Shi W S. Enforcing cooperative resource sharing in un-trusted peer-to-peer environments. Journal of Mobile Networks and Applications-Springer, 2005, 10(6): 771–783.

    Google Scholar 

  8. Liang Z Q, Shi W S. PET: A personalized trust model with reputation and risk evaluation for P2P resource sharing. In Proc. the 38th Hawaii International Conference on System Sciences, Los Alamitos, USA, Jan. 3–6, 2005, pp.201–210.

  9. Zhou R F, Hwang K. Power-Trust: A robust and scalable reputation system for trusted Peer-to-Peer computing. IEEE Trans. Parallel and Distributed Systems, 2007, 18(4): 460–473.

    Article  Google Scholar 

  10. Song S, Hwang K, Zhou R F et al. Trusted P2P transactions with fuzzy reputation aggregation. IEEE Internet Computing Magazine, Special Issue on Security for P2P and Ad Hoc Networks, Nov/Dec 2005, 9(6): 24–34.

    Article  Google Scholar 

  11. Tran T, Cohen R. Modeling reputation in agent based marketplaces to improve the performance of buying agents. In Proc. the Ninth International Conference on User Modeling (UM-03), Johnstown, PA, USA, June 22–26, 2003, pp.273–282.

  12. Cornelli F, Damiani E, Vimercati S et al. Choosing reputable servants in a P2P network. In Proc. the Eleventh International World Wide Web Conference, Hawaii, USA, Nov. 18–22, 2002, pp.376–386.

  13. Damiani E, Vimercati S, Paraboschi S et al. Managing and sharing servants' reputations in P2P systems. IEEE Trans. Knowledge and Data Engineering, 2003, 15(4): 840–854.

    Article  Google Scholar 

  14. Damiani E, Vimercati S, Paraboschi S et al. A reputation-based approach for choosing reliable resources in peer-to-peer networks. In Proc. the Ninth ACM Conference on Computer and Communications Security, Washington DC, USA, 2002, pp.207–216.

  15. Kamvar S D, Schlosser M T, Garcia M. The Eigen-Trust algorithm for reputation management in P2P networks. In Proc. the Twelfth International World Wide Web Conference, Budapest, Hungary, May 20–24, 2003, pp.640–651.

  16. Richardson M, Agrawal R, and Domingos P. Trust management for the semanticWeb. In Proc. the Second International Semantic Web Conference, Sardinia, Italy, Oct. 20–23, 2003, pp.351–368.

  17. Guha R. Propagation of trust and distrust. In Proc. the World Wide Web Conf. (WWW2004), ACM Press, New York, USA, May 19{21, 2004, pp.403–412.

  18. Buchegger S, Le B. A robust reputation system for P2P and mobile ad-hoc networks. In Proc. the 2nd Workshop Economics of Peer-to-Peer Systems, Boston, USA, June 4–5, 2004, pp.119–123.

  19. Chang J S, Wang H M, Yin G. A time-frame based trust model for P2P systems. In Proc. the 9th International Conference on Information Security and Cryptology, Busan, Korea, Nov. 30{Dec. 1, 2006, pp.155–165.

  20. Li X Y, Gui X L. Novel scalable aggregation algorithm of feedback trust information. Journal of Xi'an Jiaotong University, 2007, 41(8): 879–883.

    MATH  Google Scholar 

  21. Chase R B, Jacobs F R, Aquilano N J. Operations Management. Chase R B (eds.), New York: Mcgraw-Hill, April 2005.

  22. Song Q, Chissom B S. Forecasting enrollment with fuzzy time. Fuzzy Sets and Systems, 1993, 54(1): 1–9.

    Article  MathSciNet  Google Scholar 

  23. Yager R R. On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 1988, 18(1): 183–190.

    Article  MATH  MathSciNet  Google Scholar 

  24. Mitchell H B, Estrakh D D. A modified OWA operator and its use in Lossless DPCM image compression. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 1997, (5): 429–436.

  25. Yager R R. Induced aggregation operators. Fuzzy Sets and Systems, 2003, 137(1): 59–69.

    Article  MATH  MathSciNet  Google Scholar 

  26. Kacprzyk J, Zadrozny S. A general collective choice rule in group decision making under fuzzy preferences and fuzzy majority: An OWA operator based approach fuzzy systems. In Proc. the 2002 IEEE International Conference on Fuzzy, Honolulu, USA, May 2002, pp.1280–1285.

  27. Li X Y, Gui X L. Engineering trusted P2P system with fast reputation aggregating mechanism. In Proc. the IEEE International Conference on Robotics and Biomimetics, Sanya, China, Dec. 15–18, 2007, pp.2007–2012.

  28. Liang Z Q, Shi W S. Analysis of recommendations on trust inference in open environment. Journal of Performance Evaluation, 2008, 65(2): 99–128.

    Article  Google Scholar 

  29. Tisue S. NetLogo. 2008, http://ccl.northwestern.edu/netlogo/.

  30. Liang Z Q, Shi W S. TRECON: A framework for enforcing trusted ISP peering. In Proc. the 15th IEEE International Conference on Computer Communications and Networks (ICCCN 2006), Arlington, USA, Oct. 9–11, 2006, pp.383–389.

  31. Li X Y, Gui X L. SDT: A scalable dynamic trust model with multiple decision factors. Dynamics of Continuous Discrete and Impulsive Systems Series B: Applications & Algorithms. 2007, 14(2): 23–27.

    MathSciNet  Google Scholar 

  32. Li X Y, Gui X L. Research on adaptive prediction model of dynamic trust relationship in open distributed systems. Journal of Computational Information Systems, 2008, 4(4): 1427–1434.

    Google Scholar 

  33. Li X Y, Gui X L. Trust quantitative model with multiple decision factors in trusted network. Chinese Journal of Computers, 2009, 32(3): 405–416.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, China

    Xiao-Yong Li & Xiao-Lin Gui (Senior Member, CCF)

Authors
  1. Xiao-Yong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiao-Lin Gui
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiao-Yong Li.

Additional information

This work is supported by the National Natural Science Foundation of China under Grant No. 60873071 and the National High-Tech Research and Development 863 Program of China under Grant No. 2008AA01Z410.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, XY., Gui, XL. A Comprehensive and Adaptive Trust Model for Large-Scale P2P Networks. J. Comput. Sci. Technol. 24, 868–882 (2009). https://doi.org/10.1007/s11390-009-9278-4

Download citation

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11390-009-9278-4

Keywords

Search

Navigation