Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

A Survey on Trust Modeling from a Bayesian Perspective

Abstract

In this paper, we are concerned with trust modeling for agents in networked computing systems. As trust is a subjective notion that is invisible, implicit and uncertain in nature, many attempts have been made to model trust with aid of Bayesian probability theory, while the field lacks a global comprehensive analysis for variants of Bayesian trust models. We present a study to fill in this gap by giving a comprehensive review of the literature. A generic Bayesian trust (GBT) modeling perspective is highlighted here. It is shown that all models under survey can cast into a GBT based computing paradigm as special cases. We discuss both capabilities and limitations of the GBT perspective and point out open questions to answer for advancing it to become a pragmatic infrastructure for analyzing intrinsic relationships between variants of trust models and for developing novel models and algorithms for trust evaluation.

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

References

  1. 1.

    McKnight, D. H., & Chervany, N. L. (1996). The meanings of trust. In Technical report MISRC working paper series (Vol. 96, No. 4)

  2. 2.

    Ba, S., & Pavlou, P. (2002). Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS Quarterly, 26(3), 243–268.

  3. 3.

    Gambetta, D. (1990). Trust: Making and breaking cooperative relations. Oxford: Blackwell Pub.

  4. 4.

    McKnight, D. H., Cummings, L. L., & Chervany, N. L. (1996). Trust formation in new organizational relationships. Minneapolis: University of Minnesota.

  5. 5.

    Gambetta, D. (Ed.). (1998). Can we trust trust? In Trust: Making and breaking cooperative relations (pp. 213–237). Oxford: Blackwell.

  6. 6.

    Kini, A., & Choobineh, J. (1998). Trust in electronic commerce: definition and theoretical considerations. In Proceedings of the 31st Hawaii international conference on system sciences (Vol. 4, pp. 51–61). IEEE.

  7. 7.

    Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. F. (1998). Not so different after all: A cross-discipline view of trust. Academy of Management Review, 23(3), 393–404.

  8. 8.

    Cho, J., Chan, K., & Adali, S. (2015). A survey on trust modeling. ACM Computing Surveys, 48(2), 28.

  9. 9.

    Cahill, V., Gray, E., Seigneur, J.-M., Jensen, C. D., Chen, Y., Shand, B., et al. (2003). Using trust for secure collaboration in uncertain environments. IEEE Pervasive Computing, 2(3), 52–61.

  10. 10.

    Selvaraj, A., & Sundararajan, S. (2017). Evidence-based trust evaluation system for cloud services using fuzzy logic. International Journal of Fuzzy Systems, 19(2), 329–337.

  11. 11.

    Rafique, N., Khan, M. A., Saqib, N. A., Bashir, F., Beard, C., & Li, Z. (2016). Black hole prevention in vanets using trust management and fuzzy logic analyzer. International Journal of Computer Science and Information Security, 14(9), 1226.

  12. 12.

    Nagy, M., Vargas-Vera, M., & Motta, E. (2008). Multi agent trust for belief combination on the semantic web. In The 4th international conference on intelligent computer communication and processing (ICCP) (pp. 261–264). IEEE.

  13. 13.

    Lesani, M., & Bagheri, S. (2006). Fuzzy trust inference in trust graphs and its application in semantic web social networks. In World automation congress (WAC) (pp. 1–6). IEEE.

  14. 14.

    Chen, H., Yu, S., Shang, J., Wang, C., & Ye, Z. (2009). Comparison with several fuzzy trust methods for p2p-based system. In International conference on information technology and computer science (ITCS) (Vol. 2, pp. 188–191). IEEE.

  15. 15.

    Liao, H., Wang, Q., & Li, G. (2009). A fuzzy logic-based trust model in grid. IEEE International Conference on Networks Security Wireless Communications and Trusted Computing (NSWCTC), 1, 608–614.

  16. 16.

    Luo, J., Liu, X., Zhang, Y., Ye, D., & Xu, Z. (2008). Fuzzy trust recommendation based on collaborative filtering for mobile ad-hoc networks. In The 33rd IEEE conference on local computer networks (LCN), Citeseer (pp. 305–311).

  17. 17.

    Manchala, D. W. (1998). Trust metrics, models and protocols for electronic commerce transactions. In Proceedings of the 18th international conference on distributed computing systems (pp. 312–321). IEEE.

  18. 18.

    Nefti, S., Meziane, F., & Kasiran, K. (2005) A fuzzy trust model for e-commerce. In Proceedings of the 7th IEEE international conference on E-commerce technology (CEC) (pp. 401–404). IEEE.

  19. 19.

    Jøsang, A. (2016). Bayesian reputation systems. In Subjective logic (pp. 289–302). New York: Springer

  20. 20.

    Jiang, J., Han, G., Wang, F., Shu, L., & Guizani, M. (2015). An efficient distributed trust model for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(5), 1228–1237.

  21. 21.

    Filali, F. Z., & Yagoubi, B. (2015). Global trust: A trust model for cloud service selection. International Journal of Computer Network and Information Security, 7(5), 41.

  22. 22.

    Alhadad, N., Busnel, Y., Serrano-Alvarado, P., & Lamarre, P. (2014). Trust evaluation of a system for an activity with subjective logic. In International conference on trust, privacy and security in digital business (pp. 48–59). New York: Springer

  23. 23.

    Ahmadi, M., Gharib, M., Ghassemi, F., & Movaghar, A. (2015). Probabilistic key pre-distribution for heterogeneous mobile ad hoc networks using subjective logic. In The 29th IEEE international conference on advanced information networking and applications (AINA) (pp. 185–192). IEEE.

  24. 24.

    Cerutti, F., Kaplan, L. M., Norman, T. J., Oren, N., & Toniolo, A. (2015). Subjective logic operators in trust assessment: An empirical study. Information Systems Frontiers, 17(4), 743–762.

  25. 25.

    Liu, G., Yang, Q., Wang, H., Lin, X., & Wittie, M. P. (2014). Assessment of multi-hop interpersonal trust in social networks by three-valued subjective logic. In Proceedings of IEEE international conference on computer communications (INFOCOM) (pp. 1698–1706). IEEE.

  26. 26.

    Jøsang, A. (1999). An algebra for assessing trust in certification chains. The Network and Distributed System Security Symposium (NDSS), 99, 80–89.

  27. 27.

    Jøsang, A. (2001). A logic for uncertain probabilities. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9(03), 279–311.

  28. 28.

    Lioma, C., Larsen, B., Schütze, H., & Ingwersen, P. (2010). A subjective logic formalisation of the principle of polyrepresentation for information needs. In Proceedings of the 3rd symposium on information interaction in context (pp. 125–134). ACM.

  29. 29.

    Oren, N., Norman, T. J., & Preece, A. (2007). Subjective logic and arguing with evidence. Artificial Intelligence, 171(10–15), 838–854.

  30. 30.

    Deepa, R., & Swamynathan, S. (2014). A trust model for directory-based service discovery in mobile ad hoc networks. In International conference on security in computer networks and distributed systems (pp. 115–126). New York: Springer

  31. 31.

    Wang, J., & Sun, H. (2007). Inverse problem in DSMT and its applications in trust management. In The 1st international symposium on data, privacy, and E-commerce (ISDPE) (pp. 424–428). IEEE.

  32. 32.

    Wang, K., & Wu, M. (2007) A trust approach for node cooperation in manet. In International conference on mobile Ad-Hoc and sensor networks (pp. 481–491). New York: Springer.

  33. 33.

    Zhang, W., Zhu, S., Tang, J., & Xiong, N. (2017). A novel trust management scheme based on Dempster–Shafer evidence theory for malicious nodes detection in wireless sensor networks. The Journal of Supercomputing, 74, 1–23.

  34. 34.

    Nguyen, V., & Huynh, V. (2016). Integrating with social network to enhance recommender system based-on Dempster–Shafer theory. In International conference on computational social networks (pp. 170–181). New York: Springer.

  35. 35.

    Esposito, C., Castiglione, A., & Palmieri, F. (2018). Information theoretic-based detection and removal of slander and/or false-praise attacks for robust trust management with Dempster–Shafer combination of linguistic fuzzy terms. Concurrency and Computation: Practice and Experience

  36. 36.

    Resnick, P., Kuwabara, K., Zeckhauser, R., & Friedman, E. (2000). Reputation systems. Communications of the ACM, 43(12), 45–48.

  37. 37.

    Abdul-Rahman, A., & Hailes, S. (2000). Supporting trust in virtual communities. In Proceedings of the 33rd Hawaii international conference on system sciences (Vol. 6, pp. 6007–6016). IEEE.

  38. 38.

    Jonker, C. M., & Treur, J. (1999). Formal analysis of models for the dynamics of trust based on experiences. In European workshop on modelling autonomous agents in a multi-agent world (pp. 221–231). New York: Springer.

  39. 39.

    Jonker, C. M., Schalken, J., Theeuwes, J., & Treur, J. (2004). Human experiments in trust dynamics. In International conference on trust management (pp. 206–220). New York: Springer.

  40. 40.

    Buchegger, S., & Le Boudec, J.-Y. (2004). A robust reputation system for peer-to-peer and mobile ad-hoc networks. In The 2nd workshop on economics of peer-to-peer systems (P2PEcon) (pp. 1–6).

  41. 41.

    Pirzada, A. A. & McDonald, C. (2004). Establishing trust in pure Ad-hoc networks. In Proceedings of the 27th Australasian conference on computer science (Vol. 26, pp. 47–54). Australian Computer Society, Inc.

  42. 42.

    Sabater, J., & Sierra, C. (2001). REGRET: reputation in gregarious societies. In Proceedings of the 5th international conference on autonomous agents (pp. 194–195). ACM.

  43. 43.

    Wang, Y., & Varadharajan, V. (2005) Two-phase peer evaluation in P2P E-commerce environments. In Proceedings of IEEE international conference on e-technology, e-Commerce and e-Service (EEE) (pp. 654–657). IEEE.

  44. 44.

    Azzedin F., & Maheswaran, M. (2002). Evolving and managing trust in grid computing systems. In IEEE Canadian conference on electrical and computer engineering (CCECE) (Vol. 3, pp. 1424–1429). IEEE.

  45. 45.

    Hung, K., Lui, K., & Kwok, Y. (2007). A trust-based geographical routing scheme in sensor networks. In IEEE wireless communications and networking conference (WCNC) (pp. 3123–3127). IEEE.

  46. 46.

    Song, W., & Phoha, V. (2004). Neural network-based reputation model in a distributed system. In Proceedings of IEEE international conference on e-commerce technology (CEC) (pp. 321–324). IEEE.

  47. 47.

    Baohua, H., Heping, H., & Zhengding, L. (2005). Identifying local trust value with neural network in P2P environment. In The first IEEE and IFIP international conference in central Asia on internet (pp. 1–5). IEEE.

  48. 48.

    Songsiri, S. (2006). MTrust: a reputation-based trust model for a mobile agent system. In International conference on autonomic and trusted computing (pp. 374–385). New York: Springer.

  49. 49.

    Wang, Y., Cahill, V., Gray, E., Harris, C., & Liao, L. (2006). Bayesian network based trust management. In International conference on autonomic and trusted computing (pp. 246–257). New York: Springer.

  50. 50.

    Momani, M., Challa, S., & Alhmouz, R. (2008). BNWSN: Bayesian network trust model for wireless sensor networks. In Mosharaka international conference on communications, computers and applications (MIC-CCA) (pp. 110–115). IEEE.

  51. 51.

    Nguyen, C. T., Camp, O., & Loiseau, S. (2007). A bayesian network based trust model for improving collaboration in mobile ad hoc networks. In IEEE international conference on research, innovation and vision for the future (pp. 144–151). IEEE.

  52. 52.

    Michiardi, P., & Molva, R. (2002). Core: a collaborative reputation mechanism to enforce node cooperation in mobile ad hoc networks. In Advanced communications and multimedia security (pp. 107–121). New York: Springer.

  53. 53.

    Xiong, L., & Liu, L. (2003). A reputation-based trust model for peer-to-peer e-commerce communities. In IEEE international conference on e-commerce (CEC) (pp. 275–284). IEEE.

  54. 54.

    Jiang, T., & Baras, J. S. (2004) Ant-based adaptive trust evidence distribution in MANET. In Proceedings of the 24th international conference on distributed computing systems workshops (pp. 588–593). IEEE.

  55. 55.

    Wang, W., Zeng, G., & Yuan, L. (2006). Ant-based reputation evidence distribution in P2P networks. In The 5th international conference grid and cooperative computing (GCC) (pp. 129–132). IEEE.

  56. 56.

    Mármol, F. G., & Pérez, G. M. (2011). Providing trust in wireless sensor networks using a bio-inspired technique. Telecommunication Systems, 46(2), 163–180.

  57. 57.

    Marmol, F. G., Perez, G. M., & Skarmeta, A. (2009). TACS, a trust model for P2P networks. Wireless Personal Communications, 51(1), 153–164.

  58. 58.

    Santos, N., Rodrigues, R., Gummadi, K. P., & Saroiu, S. (2012) Policy-sealed data: A new abstraction for building trusted cloud services. In USENIX security symposium (pp. 175–188).

  59. 59.

    Neuman, B. C., & Ts’o, T. (1994). Kerberos: An authentication service for computer networks. IEEE Communications Magazine, 32(9), 33–38.

  60. 60.

    Winslett, M., Yu, T., Seamons, K. E., Hess, A., Jacobson, J., Jarvis, R., et al. (2002). Negotiating trust in the web. IEEE Internet Computing, 6(6), 30–37.

  61. 61.

    Li, N., Winsborough, W. H., & Mitchell, J. C. (2003). Distributed credential chain discovery in trust management. Journal of Computer Security, 11(1), 35–86.

  62. 62.

    Nejdl, W., Olmedilla, D., & Winslett, M. (2004). Peertrust: Automated trust negotiation for peers on the semantic web. In Workshop on secure data management (pp. 118–132). New York: Springer.

  63. 63.

    Bonatti, P., & Olmedilla, D. (2005). Driving and monitoring provisional trust negotiation with metapolicies. In The 6th IEEE international workshop on policies for distributed systems and networks (pp. 14–23). IEEE.

  64. 64.

    Winsborough, W. H., Seamons, K. E., & Jones, V. E. (2000). Automated trust negotiation. In Proceedings of DARPA information survivability conference and exposition (DISCEX) (Vol. 1, pp. 88–102). IEEE.

  65. 65.

    Becker, M. Y., & Sewell, P. (2004). Cassandra: Distributed access control policies with tunable expressiveness. In Proceedings of the 5th IEEE international workshop on policies for distributed systems and networks (POLICY) (pp. 159–168). IEEE.

  66. 66.

    Olmedilla, D. (2007). Security and privacy on the semantic web. In Security, privacy, and trust in modern data management (pp. 399–415). New York: Springer.

  67. 67.

    Lee, M. K., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75–91.

  68. 68.

    Theodorakopoulos, G., & Baras, J. S. (2006). On trust models and trust evaluation metrics for ad hoc networks. IEEE Journal on Selected Areas in Communications, 24(2), 318–328.

  69. 69.

    Bao, F., Chen, R., Chang, M., & Cho, J.-H. (2012). Hierarchical trust management for wireless sensor networks and its applications to trust-based routing and intrusion detection. IEEE Transactions on Network and Service Management, 9(2), 169–183.

  70. 70.

    Boukerche, A., & Ren, Y. (2008). A trust-based security system for ubiquitous and pervasive computing environments. Computer Communications, 31(18), 4343–4351.

  71. 71.

    Kamvar, S. D., Schlosser, M. T., & Garcia-Molina, H. (2003) The eigentrust algorithm for reputation management in P2P networks. In Proceedings of the 12th international conference on World Wide Web (pp. 640–651). ACM.

  72. 72.

    Xiong, L., & Liu, L. (2004). Peertrust: Supporting reputation-based trust for peer-to-peer electronic communities. IEEE Transactions on Knowledge and Data Engineering, 16(7), 843–857.

  73. 73.

    Regan, K., & Cohen, R. (2005). A model of indirect reputation assessment for adaptive buying agents in electronic markets. Proceedings of the business agents and semantic web (BASeWEB) (pp. 41–51).

  74. 74.

    Zacharia, G., & Maes, P. (2000). Trust management through reputation mechanisms. Applied Artificial Intelligence, 14(9), 881–907.

  75. 75.

    Su, X., Zhang, M., Mu, Y., & Sim, K. M. (2010). PBTrust: A priority-based trust model for service selection in general service-oriented environments. In IEEE/IFIP 8th international conference on embedded and ubiquitous computing (EUC) (pp. 841–848). IEEE.

  76. 76.

    Zouridaki, C. (2007). Trust establishment for reliable data packet delivery in mobile ad hoc networks

  77. 77.

    Liu, B., Xu, Z., Chen, J., & Yang, G. (2015). Toward reliable data analysis for internet of things by Bayesian dynamic modeling and computation. In IEEE China summit and international conference on signal and information processing (ChinaSIP) (pp. 1027–1031). IEEE.

  78. 78.

    Liu, B., & Yang, G. (2015). Probabilistic trust evaluation with inaccurate reputation reports. International Journal of Distributed Sensor Networks, 11(6), 1–7.

  79. 79.

    Denko, M. K., Sun, T., & Woungang, I. (2011). Trust management in ubiquitous computing: A Bayesian approach. Computer Communications, 34, 398–406.

  80. 80.

    Liu, Bin, & Cheng, Shi. (2017). State space model based trust evaluation over wireless sensor networks: An iterative particle filter approach. Journal of Engineering, 2017(4), 101–109.

  81. 81.

    Chen, R., Bao, F., Chang, M., & Cho, J.-H. (2014). Dynamic trust management for delay tolerant networks and its application to secure routing. IEEE Transactions on Parallel and Distributed Systems, 25(5), 1200–1210.

  82. 82.

    Wang, Y., & Vassileva, J. (2003). Bayesian network-based trust model. In Proceedings of IEEE/WIC international conference on web intelligence (WI) (pp. 372–378). IEEE.

  83. 83.

    Dubey, J., & Tokekar, V. (2014) Bayesian network based trust model with time window for pure P2P computing systems. In IEEE global conference on wireless computing and networking (GCWCN) (pp. 219–223). IEEE.

  84. 84.

    Venanzi, M., Teacy, W. L., Rogers, A., & Jennings, N. R. (2015). Bayesian modelling of community-based multidimensional trust in participatory sensing under data sparsity. In IJCAI (pp. 717–724).

  85. 85.

    Xu, A., & Dudek, G. (2015). Optimo: Online probabilistic trust inference model for asymmetric human-robot collaborations. In Proceedings of the 10th annual ACM/IEEE international conference on human–robot interaction (pp. 221–228). ACM.

  86. 86.

    Guo, J., Chen, R., & Tsai, J. (2017). A survey of trust computation models for service management in internet of things systems. Computer Communications, 97, 1–14.

  87. 87.

    Yan, Z., Zhang, P., & Vasilakos, A. V. (2014). A survey on trust management for Internet of things. Journal of Network and Computer Applications, 42, 120–134.

  88. 88.

    Jøsang, A., Ismail, R., & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. Decision Support Systems, 43(2), 618–644.

  89. 89.

    Zhang, J. (2011). A survey on trust management for vanets. In IEEE international conference on advanced information networking and applications (AINA) (pp. 105–112). IEEE.

  90. 90.

    Viljanen, L. (2005). Towards an ontology of trust. In International conference on trust, privacy and security in digital business (pp. 175–184). New York: Springer.

  91. 91.

    Artz, D., & Gil, Y. (2007). A survey of trust in computer science and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 5(2), 58–71.

  92. 92.

    Yu, H., Shen, Z., Miao, C., Leung, C., & Niyato, D. (2010). A survey of trust and reputation management systems in wireless communications. Proceedings of the IEEE, 98(10), 1755–1772.

  93. 93.

    Momani, M., & Challa, S. (2010). Survey of trust models in different network domains. International Journal of Ad Hoc and Ubiquitous Computing, 1(3), 1–19.

  94. 94.

    Momani, M. (2010). Trust models in wireless sensor networks: A survey. In International conference on network security and applications (pp. 37–46). New York: Springer.

  95. 95.

    Grandison, T., & Sloman, M. (2000). A survey of trust in internet applications. IEEE Communications Surveys and Tutorials, 3(4), 2–16.

  96. 96.

    Sherchan, W., Nepal, S., & Paris, C. (2013). A survey of trust in social networks. ACM Computing Surveys, 45(4), 47.

  97. 97.

    Pinyol, I., & Sabater-Mir, J. (2013). Computational trust and reputation models for open multi-agent systems: A review. Artificial Intelligence Review, 40(1), 1–25.

  98. 98.

    Lopez, J., Roman, R., Agudo, I., & Fernandez-Gago, C. (2010). Trust management systems for wireless sensor networks: Best practices. Computer Communications, 33(9), 1086–1093.

  99. 99.

    Arulampalam, M. S., Maskell, S., Gordon, N., & Clapp, T. (2002). A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transaction on Signal Processing, 50(2), 174–188.

  100. 100.

    Liu, B. (2011). Instantaneous frequency tracking under model uncertainty via dynamic model averaging and particle filtering. IEEE Transsction on Wireless Communications, 10(6), 1810–1819.

  101. 101.

    Liu, B., Ji, C., Zhang, Y., Hao, C., & Wong, K. (2010). Multi-target tracking in clutter with sequential Monte Carlo methods. IET Radar, Sonar & Navigation, 4(5), 662–672.

  102. 102.

    Liu, B., & Hao, C. (2013). Sequential bearings-only-tracking initiation with particle filtering method. The Scientific World Journal, 2013, 1–7.

  103. 103.

    Liu, B., Ma, X., Hou, C. (2008). A particle filter using SVD based sampling Kalman filter to obtain the proposal distribution. In Proceedings of IEEE conference on cybernetics and intelligent systems (pp. 581–584). IEEE.

  104. 104.

    Liu, B. (2017). Robust particle filter by dynamic averaging of multiple noise models. In Proceeding of the 42nd IEEE international conference on acoustics, speech, and signal processing (ICASSP) (pp. 4034–4038). IEEE.

  105. 105.

    Dai, Y., & Liu, B. (2016). Robust video object tracking via Bayesian model averaging-based feature fusion. Optical Engineering, 55(8), 083102(1)–083102(11).

  106. 106.

    Jøsang, A., & Ismail, R. (2002). The beta reputation system. In Proceedings of the 15th BLED electronic commerce conference (Vol. 5, pp. 2502–2511).

  107. 107.

    Teacy, W. L., Patel, J., Jennings, N. R., & Luck, M. (2005). Coping with inaccurate reputation sources: Experimental analysis of a probabilistic trust model. In Proceedings of the 4th international joint conference on autonomous agents and multiagent systems (pp. 997–1004). ACM.

  108. 108.

    Teacy, W. L., Patel, J., Jennings, N. R., & Luck, M. (2006). Travos: Trust and reputation in the context of inaccurate information sources. Autonomous Agents and Multi-agent Systems, 12(2), 183–198.

  109. 109.

    Huynh, T. D., Jennings, N. R., & Shadbolt, N. R. (2006). An integrated trust and reputation model for open multi-agent systems. Autonomous Agents and Multi-agent Systems, 13(2), 119–154.

  110. 110.

    Patel, J., Teacy, W. L., Jennings, N. R., & Luck, M. (2005). A probabilistic trust model for handling inaccurate reputation sources. International conference on trust management (pp. 193–209). New York: Springer.

  111. 111.

    Teacy, W. L., Jennings, N. R., Rogers, A., & Luck, M. (2008). A hierarchical Bayesian trust model based on reputation and group behaviour. In Proceedings of 6th European workshop on multi-agent systems (pp. 1–15).

  112. 112.

    Whitby, A., Jøsang, A. & Indulska, J. (2004). Filtering out unfair ratings in Bayesian reputation systems. In Proceedings of the 7th international workshop on trust in agent societies (Vol. 6, pp. 106–117).

  113. 113.

    Zhang, J., & Cohen, R. (2008). Evaluating the trustworthiness of advice about seller agents in e-marketplaces: A personalized approach. Electronic Commerce Research and Applications, 7(3), 330–340.

  114. 114.

    Mui, L., Mohtashemi, M., & Halberstadt, A. (2002). A computational model of trust and reputation. In Proceedings of the 35th annual Hawaii international conference on system sciences (HICSS) (pp. 2431–2439). IEEE.

  115. 115.

    Despotovic, Z., & Aberer, K. (2006). P2p reputation management: Probabilistic estimation versus social networks. Computer Networks, 50(4), 485–500.

  116. 116.

    Nielsen, M., Krukow, K., & Sassone, V. (2007). A Bayesian model for event-based trust. Electronic Notes in Theoretical Computer Science, 172, 499–521.

  117. 117.

    Reece, S., Rogers, A., Roberts, S., & Jennings, N. R. (2007). Rumours and reputation: evaluating multi-dimensional trust within a decentralised reputation system. In Proceedings of the 6th international joint conference on autonomous agents and multiagent systems (p. 165). ACM.

  118. 118.

    Regan, K., Poupart, P., & Cohen, R. (2006). Bayesian reputation modeling in e-marketplaces sensitive to subjectivity, deception and change. In Proceedings of the National Conference on Artificial Intelligence (Vol. 21, p. 1206). London: AAAI Press.

  119. 119.

    Wang, J., & Liu, B. (2017). Online fault-tolerant dynamic event region detection in sensor networks via trust model. In IEEE wireless communications and networking conference (WCNC) (pp. 1–6). IEEE.

  120. 120.

    Jøsang, A. (1997). Artificial reasoning with subjective logic. In Proceedings of the 2nd Australian workshop on commonsense reasoning (Vol. 48, p. 34).

  121. 121.

    Ivanovska, M., Jøsang, A., Zhang, J., & Chen, S. (2017). Joint subjective opinions. In Modeling decisions for artificial intelligence (pp. 220–233). New York: Springer.

  122. 122.

    Pope, S., & Jøsang, A. (2005). Analysis of competing hypotheses using subjective logic. In Technical report, Queensland University Brisbane.

  123. 123.

    Ivanovska, M., Jøsang, A., & Sambo, F. (2016). Bayesian deduction with subjective opinions. In The 15th international conference on principles of knowledge representation and reasoning (KR) (pp. 484–493).

  124. 124.

    Jøsang, A. (2008). Conditional reasoning with subjective logic. Journal of Multiple-Valued Logic and Soft Computing, 15(1), 5–38.

  125. 125.

    Jøsang, A., & Hankin, R. (2012). Interpretation and fusion of hyper opinions in subjective logic. In The 15th international conference on information fusion (FUSION) (pp. 1225–1232). IEEE.

  126. 126.

    Jøsang, A., Wang, D., & Zhang, J. (2017). Multi-source fusion in subjective logic. In Proceedings of FUSION.

  127. 127.

    Jøsang, A., & Kaplan, L. (2016). Principles of subjective networks. In The 19th international conference on information fusion (FUSION) (pp. 1292–1299). IEEE.

  128. 128.

    Jøsang, A., Hayward, R., & Pope, S. (2006). Trust network analysis with subjective logic. In Proceedings of the 29th Australasian computer science conference (Vol. 48, pp. 85–94). Australian Computer Society, Inc.

  129. 129.

    Jøsang, A., & Bhuiyan, T. (2008). Optimal trust network analysis with subjective logic. In The 2nd international conference on emerging security information, systems and technologies (SECURWARE) (pp. 179–184). IEEE.

  130. 130.

    Liu, Y., Li, K., Jin, Y., Zhang, Y., & Qu, W. (2011). A novel reputation computation model based on subjective logic for mobile ad hoc networks. Future Generation Computer Systems, 27(5), 547–554.

  131. 131.

    Kaplan, L., & Ivanovska, M. (2016). Efficient subjective Bayesian network belief propagation for trees. In The 19th international conference on information fusion (FUSION) (pp. 1–8). IEEE.

  132. 132.

    Kaplan, L., Sensoy, M., Tang, Y., Chakraborty, S., Bisdikian, C., & de Mel, G. (2013). Reasoning under uncertainty: Variations of subjective logic deduction. In 16th international conference on information fusion (FUSION) (pp. 1910–1917). IEEE.

  133. 133.

    Wang, Y., & Vassileva, J. (2003). Bayesian network trust model in peer-to-peer networks. In Moro G., Sartori C., & Singh M. P. (Eds.), Lecture notes in computer science, agents and peer-to-peer computing (AP2PC 2003) (Vol. 2872, pp. 23–34). New York: Springer.

  134. 134.

    Resnick, P., & Zeckhauser, R. (2002). Trust among strangers in internet transactions: Empirical analysis of ebay’s reputation system. Advances in Applied Microeconomics, 11, 127–157.

  135. 135.

    Zhou, R., & Hwang, K. (2007). Powertrust: A robust and scalable reputation system for trusted peer-to-peer computing. IEEE Transactions on Parallel and Distributed Systems, 18(4), 460–473.

  136. 136.

    Ries, S., Habib, S. M., Mühlhäuser M., & Varadharajan, V. (2011). Certainlogic: A logic for modeling trust and uncertainty. In International conference on trust and trustworthy computing (Vol. 6740, pp. 254–261). New York: Springer.

  137. 137.

    Wang, Y., & Vassileva, J. (2003). Trust and reputation model in peer-to-peer networks. In Proceedings of the 3rd international conference on peer-to-peer computing (pp. 150–157).

  138. 138.

    Berger, J. O. (2013). Statistical decision theory and Bayesian analysis. New York: Springer.

Download references

Acknowledgements

This work was partly supported by National key research and development plan of China (No.YFB2101704), National Natural Science Foundation of China (Nos. 61571238, 61572263, and 61906099).

Author information

Correspondence to Bin Liu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Liu, B. A Survey on Trust Modeling from a Bayesian Perspective. Wireless Pers Commun (2020). https://doi.org/10.1007/s11277-020-07097-5

Download citation

Keywords

  • Bayesian
  • Networked computing systems
  • Trust evaluation
  • Trust modeling