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A Trustworthy Group Identifying Trust Metric for P2P Service Sharing Economy Based on Personal Social Network of Users

  • Computer Science
  • Published:
Wuhan University Journal of Natural Sciences

Abstract

With the quick growth of sharing economy, service sharing becomes a popular phenomenon in daily lives. However, some service providers give exaggerated information about their services on the Peer-to-Peer (P2P) service sharing platforms to get more profits. How to identify a reliable service provider becomes a difficult challenge for users. In this paper, we propose a trustworthy group trust metric for P2P service sharing (TMPSS) economy based on personal social network (PSN) of users. Deriving from Advogato group trust metric, it considers factors such as social circle similarity, preference similarity, interaction degree, ranks the reliable nodes in a target user’s PSN, outputs an ordered set of reliable nodes, and prevents unreliable nodes from access PSN of honest users. Experimental results show that TMPSS has advantages over existing representative methods because it finds more reliable nodes, and counts against malicious nodes’ attacks more effectively, and it is suitable for mobile transaction circumstances.

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References

  1. Puschmann T, Alt R. Sharing economy[J]. Business & Information Systems Engineering, 2016, 58(1): 93–99.

    Article  Google Scholar 

  2. Shore S H. For better, for worse: Intra-household risk-sharing over the business cycle[J]. Review of Economics & Statistics, 2010, 92(3): 536–548.

    Article  Google Scholar 

  3. Hamari J, Sjöklint M, Ukkonen A. The sharing economy: Why people participate in collaborative consumption[J]. Journal of the Association for Information Science and Technology, 2016, 67(9): 2047–2059.

    Article  Google Scholar 

  4. Hasan R, Birgach M. Critical success factors behind the sustainability of the sharing economy[C]//IEEE, International Conference on Software Engineering Research, Management and Applications. Washington D C: IEEE, 2016: 287–293.

    Google Scholar 

  5. Hawlitschek F, Lippert F. Whom to trust? Assessing the role of profile pictures on sharing economy platforms[C]//International Conference on Group Decision & Negotiation. Washington D C: IEEE, 2015: 306–323.

    Google Scholar 

  6. Dillahunt T, Lampinen A, O’Neill J, et al. Does the sharing economy do any good?[C]//ACM Conference on Computer Supported Cooperative Work and Social Computing Companion. New York: ACM, 2016: 197–200.

    Google Scholar 

  7. Ert E, Fleischer A, Magen N. Trust and reputation in the sharing economy: the role of personal photos in Airbnb[J]. Tourism Management, 2016, 55(1): 62–73.

    Article  Google Scholar 

  8. Tahta U E, Sen S, Can A B. GenTrust: A genetic trust management model for peer-to-peer systems[J]. Applied Soft Computing, 2015, 34: 693–704.

    Article  Google Scholar 

  9. Jiang L, Xu J, Zhang K, et al. A new evidential trust model for open distributed systems[J]. Expert Systems with Applications, 2012, 39(3): 3772–3782.

    Article  Google Scholar 

  10. Lax G, Sarné G M L. CellTrust: a reputation model for C2C commerce[J]. Electronic Commerce Research, 2008, 8(4): 193–216.

    Article  Google Scholar 

  11. Acampora G, Alghazzawi D, Hagras H, et al. An interval type-2 fuzzy logic based framework for reputation management in peer-to-peer e-commerce[J]. Information Sciences, 2016, 333(C): 88–107.

    Article  Google Scholar 

  12. Zhang J, Cohen R. A framework for trust modeling in multiagent electronic marketplaces with buying advisors to consider varying seller behavior and the limiting of seller bids[J]. ACM Transactions on Intelligent Systems & Technology, 2013, 4(2): 1–22.

    Article  Google Scholar 

  13. Koll D, Li J, Fu X. SOUP: An online social network by the people, for the people[C]//ACM Conference on SIGCOMM. New York: ACM, 2015: 143–144.

    Google Scholar 

  14. Yan S R, Zheng X L, Wang Y, et al. A graph-based comprehensive reputation model[J]. Information Sciences, 2015, 318(C): 51–72.

    Article  Google Scholar 

  15. Ruan Y, Durresi A. A survey of trust management systems for online social communities—Trust modeling, trust inference and attacks[J]. Knowledge-Based Systems, 2016, 106(2): 150–163.

    Article  Google Scholar 

  16. Yu H, Shen Z, Leung C, et al. A survey of multi-agent trust management systems[J]. IEEE Access, 2013, 1(1): 35–50.

    Google Scholar 

  17. Zolfaghar K, Aghaie A. A syntactical approach for interpersonal trust prediction in social web applications: Combining contextual and structural data[J]. Knowledge-Based Systems, 2012, 26(1): 93–102.

    Article  Google Scholar 

  18. Hur J, Guo M, Park Y, et al. Reputation-Based collusion detection with majority of colluders[J]. Ieice Transactions on Information & Systems, 2016, E99. D(7): 1822–1835.

    Article  Google Scholar 

  19. Al-Oufi S, Kim H N, El Saddik A. A group trust metric for identifying people of trust in online social networks[J]. Expert Systems with Applications, 2012, 39(18): 13173–13181.

    Article  Google Scholar 

  20. Ford L R, Fulkerson D R. Maximal Flow Through a Network: Classic Papers in Combinatorics[M]. Boston: Birkhäuser, 2009: 243–248.

    Google Scholar 

  21. Granovetter M. The strength of weak ties: A network theory revisited[J]. Sociological Theory, 1983, 1(1): 201–233.

    Article  Google Scholar 

  22. Gilbert T E, Karahalios K. Predicting tie strength with social media[C]//International Conference on Human Factors in Computing Systems. New York: ACM, 2009: 211–220.

    Google Scholar 

  23. Kleinberg J. The small-world phenomenon: An algorithmic perspective[J]. Proceedings of ACM Symposium on Theory of Computing, 2010, 406(2): 163–170.

    Google Scholar 

  24. Tong H, Faloutsos C, Pan J Y. Fast random walk with restart and its applications[C]//International Conference on Data Mining. Washington D C: IEEE, 2006: 613–622.

    Google Scholar 

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Correspondence to Wenqiang Zhu.

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Foundation item: Supported by the National Social Science Foundation of China(17BGL201)

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Zhu, W. A Trustworthy Group Identifying Trust Metric for P2P Service Sharing Economy Based on Personal Social Network of Users. Wuhan Univ. J. Nat. Sci. 23, 139–149 (2018). https://doi.org/10.1007/s11859-018-1304-3

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  • DOI: https://doi.org/10.1007/s11859-018-1304-3

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