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A Survey on Trust Modeling from a Bayesian Perspective


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.

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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).

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Correspondence to Bin Liu.

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

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