  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.
