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A Collaborative Reputation System Based on Credibility Propagation in WSNs

Trust and reputation systems are widely employed in WSNs to help decision making processes by assessing trustworthiness of sensor nodes in a data aggregation process. However, in unattended and hostile environments, more sophisticated malicious attacks, such as collusion attacks, can distort the computed trust scores and lead to low quality or deceptive service as well as undermine the aggregation results. In this paper we propose a novel, local, collaborative-based trust framework for WSNs that is based on the concept of credibility propagation which we introduce. In our approach, trustworthiness of a sensor node depends on the amount of credibility that such a node receives from other nodes. In the process we also obtain an estimates of sensors' variances which allows us to estimate the true value of the signal using the Maximum Likelihood Estimation. Extensive experiments using both real-world and synthetic datasets demonstrate the efficiency and effectiveness of our approach.