An Efficient Trust Evaluation Scheme for Node Behavior Detection in the Internet of Things

In the Internet of things, trust establishment plays an important role of improving cooperation and enhancing security. To evaluate the trust relationships among sensor nodes accurately, an appropriate trust estimation model should be designed so as to against attack and misbehavior effectively. In this paper, a novel quantitative model of trust value is proposed. A variety of trust factors related to the behaviors of sensor nodes is measured, including the packet forwarding capacity, the repetition rate, the consistency of the packet content, the delay, the integrity, etc. To void the impact of subjective setting, each trust factor is determined by means of the information entropy theory. In addition, the D-S theory is adopted to deduce and synthesize the trust, and the statistic factor of nodes’ behavior is introduced to modify the synthesis result. Evaluation results show that our scheme performs better in defeating attacks.