Wang, Y, Cahill, V, Gray, E, Harris, C, Liao, L., Bayesian network based trust management, Lecture Notes in Computer Science , Autonomic and Trusted Computing, Wuhan and Three Gorges, China, September, 4158, Springer Berlin / Heidelberg, 2006, 246-257
Trust is an essential component for secure collaboration in uncertain
environments. Trust management can be used to reason about future interactions
between entities. In reputation-based trust management, an entity’s reputation is
usually built on ratings from those who have had direct interactions with the entity.
In this paper, we propose a Bayesian network based trust management model.
In order to infer trust in dierent aspects of an entity’s behavior, we use multidimensional
application specific trust values and each dimension is evaluated using
a single Bayesian network. This makes it easy both to extend the model to
involve more dimensions of trust and to combine Bayesian networks to form an
opinion about the overall trustworthiness of an entity. Each entity can evaluate his
peers according to his own criteria. The dynamic characteristics of criteria and of
peer behavior can be captured by updating Bayesian networks. Risk is explicitly
combined with trust to help users making decisions. In this paper, we show that
our system can make accurate trust inferences and is robust against unfair raters.
PUBLISHED Wuhan and Three Gorges, China Track 2: Trust Models and Trustworthy Systems/Services
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