A Credible Bayesian-Based Trust Management Scheme for Wireless Sensor Networks

With the rapid development of wireless sensor networks (WSNs), the security of WSNs is an important issue in this field because of their vulnerabilities to attacks. Designing a reasonable trust management scheme that can evaluate the trust relationships among sensor nodes accurately is a challenging but meaningful task. In this paper, a credible Bayesian-based trust management scheme (BTMS) is proposed. The overall trust value is aggregated by both direct and indirect trust information. The former is calculated by a modified Bayesian equation and updated by a sliding window. The latter is computed by recommendations from a third party. Moreover, the indirect trust computation is invoked conditionally according to the uncertainty of direct trust calculated via Entropy Theory and malicious feedbacks are excluded. Meanwhile, different recommendations are appropriately weighted in light of the trust levels of recommenders. Simulations are conducted and the results show that, compared with existing approaches, the proposed trust model performs better in defeating attacks.