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We propose a context-aware trust management model called CATrust for service-oriented ad hoc networks such as peer-to-peer and Internet of Things networks wherein a node can be a service requester or a service provider. The novelty of our design lies in the use of logistic regression to dynamically estimate trustworthiness of a service provider based on its service behavior patterns in response to context environment changes. We develop a recommendation filtering mechanism to effectively screen out dishonest recommendations even in extremely hostile environments in which the majority recommenders are dishonest. We demonstrate desirable convergence, accuracy, and resiliency properties of CATrust. We also demonstrate that CATrust outperforms contemporary peer-to-peer and Internet of Things trust models in terms of service trust prediction accuracy against collusion recommendation attacks.
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Wang et al. (2016) studied this question.
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