An Effective Exponential-Based Trust and Reputation Evaluation System in Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) are vulnerable to many security threats from compromised nodes, and because the WSNs are resource-constrained, the traditional security methods cannot be used to resist the internal attacks from compromised nodes. The trust and reputation evaluation system is the most effective security mechanisms to protect WSNs from internal attacks. The exponential-based trust and reputation evaluation system (ETRES) is proposed for WSNs' node trust and reputation evaluation. ETRES is used to observe the nodes' behavior, and exponential distribution is applied to represent the distribution of nodes' trust. The trust of the node is used to look for reliable nodes to transmit data and weaken malicious attacks within the wireless sensor networks. More significantly, the entropy theory is used to measure the uncertainty of direct trust values in this paper. Indirect trust is introduced to strengthen interaction information when the uncertainty of direct trust is enough high. It can not only reduce the computing power of nodes but also prolong the lifetime of the network. In addition, the confidence factor is redefined, which can dynamically adjust the node trust value to weaken the harmful effects of the compromised nodes. The simulation results show that the proposed system can more effectively defend the internal attack than the beta-based trust and reputation evaluation system (RFSN) and the binomial-based trust management System (BTMS). The proposed method can be used to strengthen network security by selecting reliable nodes. What is more, the information trust and energy are prone to integrate into ETRES.

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