A novel trust model of dynamic optimization based on entropy method in wireless sensor networks

作者：Nie, Shuzhi^*

来源：Cluster Computing, 2019, 22(S5): 11153-11162.

DOI：10.1007/s10586-017-1337-y

• Wireless sensor networks
• Public key infrastructure
• Malicious nodes
• Information entropy
• Trust evaluation

With the continuous development of wireless sensor networks (WSNs), the existence of malicious nodes poses a great threat to the security of the system. In traditional models based on reputation threshold, the malicious nodes can not be identified accurately with the result of low recognition rate and high false positive rate. To solve the problems of dynamic characteristic and deal with collusion attack in WSNs, a novel trust model of dynamic optimization based on entropy method (Trust-Doe) is proposed. The model is based on the global trust degree of nodes, and logically divides nodes into different groups. Then, the entropy and weight values of the group are calculated based on the entropy weight method, and the local trust degree of the nodes is updated periodically. Finally, the reputation standard deviation of the local evaluation for different groups and local evaluation standard deviation can be obtained, and the dynamic optimization competition strategy will be taken effect to improve the accuracy of trust model. Simulation results show that the improved algorithm is very effective to identify malicious nodes without obvious features.

• 出版日期2019-9
• 单位江门职业技术学院