Construction of Internet of things trusted group based on multidimensional attribute trust model

Accurate prediction of the trust relationship is the basis for trusted access and secure interaction between Internet of things nodes. To evaluate the degree of trust, a trust metric is assigned to every node depending on its several attributes. Normal nodes in Internet of things tend to suffer collusion attacks from malicious nodes; thus, the accuracy of the trust measurement decreases. To enhance the security of interaction between massive Internet of things nodes, we propose a multidimensional attribute trust model and a dynamic maintenance mechanism of a trusted group. The proposed model provides a reference for the selection and evaluation of node multidimensional attribute factors to adapt to different Internet of things application scenarios. The dispersion of satisfaction records is used to discover abnormal data and weaken its influence on the calculation of the node’s comprehensive trust evaluation. The construction of trusted groups provides an architectural foundation for the application of group signature that maintains low network overhead. The performance of multidimensional attribute trust model and dynamic maintenance mechanism is verified using Netlogo. Simulation results show the efficiency of the proposed model to classify the malicious nodes and honest nodes, as well as to build a trusted group that could ensure honest nodes occupy the major proportion.