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, with a hope to advance GBT to become a pragmatic infrastructure for analyzing intrinsic relationships among variants of trust models and developing novel tools for trust evaluation.

中文翻译：

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贝叶斯视角下的信任建模综述

在本文中，我们关注网络计算系统中代理的信任建模。由于信任是一个主观的概念，在本质上是不可见的、隐含的和不确定的，许多尝试借助贝叶斯概率论对信任进行建模，而该领域缺乏对贝叶斯信任模型变体的全局综合分析。我们提出了一项研究，通过对文献进行全面回顾来填补这一空白。此处突出显示了通用贝叶斯信任 (GBT) 建模观点。结果表明，调查中的所有模型都可以作为特殊情况转换为基于 GBT 的计算范式。我们讨论了 GBT 视角的能力和局限性，并指出了要回答的开放性问题，