A Dynamic Bayesian-Based Comprehensive Trust Evaluation Model for Dispersed Computing Environment

Dispersed computing is a new resource -centric computing paradigm. Due to its high degree of openness and decentralization, it is vulnerable to at-tacks, and security issues have become an important challenge hindering its development. The trust evalu-ation technology is of great significance to the reliable operation and security assurance of dispersed comput-ing networks. In this paper, a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment. Specifically, in the calculation of direct trust, a logarithmic decay func-tion and a sliding window are introduced to improve the timeliness. In the calculation of indirect trust, a random screening method based on sine function is designed, which excludes malicious nodes provid-ing false reports and multiple malicious nodes collud-ing attacks. Finally, the comprehensive trust value is dynamically updated based on historical interactions, current interactions and momentary changes. Simula-tion experiments are introduced to verify the perfor-mance of the model. Compared with existing model, the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes, the in-teraction success rate, and the computational cost.