A Trustworthiness Evaluation Method for Wireless Sensor Nodes Based on D-S Evidence Theory

As many wireless sensor networks (WSNs) are deployed in complicated environment without good physical protection, the sensor nodes are more vulnerable to be affected by uncertain factors from inside or outside so that the sensed data always cannot reflect the real world situation well. Thus the trustworthiness of sensor nodes should be evaluated for revising the faulty ones in after-deployment maintenances. In this paper, we propose a trustworthiness evaluation method based on D-S evidence theory in data level for sensor nodes which can sense multi-dimensional data. Different dimensions of a sensor node are regarded as its different trustworthiness attributes in this method. For a single node, the trustworthiness of each attribute is evaluated firstly based on evidence theory, and then the lower and upper limits of trust degree for this node are calculated by fusing the evaluation results of different attributes. Moreover, in order to figure out whether regional uncertain factors exist or not, the trust degree of a local region is given by fusing the judgments of deployed sensor nodes according to the combination rules of evidence theory. Extensive experiments based on actual data samples are conducted to evaluate the performance of our method. The theoretical analysis and experimental results show that our method can give effective trustworthiness evaluation for one single sensor node or a local region. Also, robustness and stability of this method are verified in the experiments.