Abstract: Aiming at the accuracy and time overhead of device trust evaluation in edge computing environment, a dynamic trust evaluation model for edge devices is proposed. Firstly, the time-degradation factor is used to express the degree of direct trust invalidity, the satisfaction function is introduced to modify the Bayesian equation, and the incentive mechanism is used to evaluate the direct trust between edge devices. Secondly, the improved grey correlation analysis method is used to determine the index weight to solve the problem of recommending equipment weight in the process of indirect trust evaluation. Finally, through the information entropy fusion of direct trust and indirect trust, the comprehensive trust value of the device is obtained, and the dynamic update factor is used to dynamically update the integrated trust value. The simulation analysis shows that, compared with the RFSN model, the proposed model can reduce the false detection rate of malicious devices by 5.7% on average, and increase the inter-device interaction success rate by 4.1%. At the same time, it is verified that the trust evaluation model is superior to the FHTM model and the RFSN model in terms of time overhead, which can more accurately and efficiently evaluate the trust of edge devices.

Key words: edge computing, trust evaluation, time-degradation factor, grey relational analysis