Power system terminal continuous trust evaluation model based on fine-grained data flow analysis
Ming hui Xie · 2022
With the wide application of new power services, the continuous strengthening of plant network coordination and interaction, resulting in a large extension of data network, network security protection is more difficult. We propose a power system terminal continuous trust evaluation model based on fine-grained data flow analysis, which effectively solves the problem of weak anti-jamming of traditional trust evaluation and unstable trust evaluation results through the analysis of the context behavior of the access subject, evidence reasoning, and identification of intent of confidence propagation. Innovative application of natural language processing (NLP) technology to Web application traffic intrusion detection, multi-level, multi-grained traffic depth analysis, dynamic intelligent correlation and drilling analysis for network traffic data, reduce the traditional feature-based and reputation detection technology leakage rate, the location, tracking and traceability of abnormal traffic, the accuracy of the detection results reached 96.59 percent.