Power system terminal continuous trust evaluation model based on fine-grained data flow analysis

Ming Xie

doi:10.1117/12.2626908

2 March 2022 Power system terminal continuous trust evaluation model based on fine-grained data flow analysis

Ming Xie

Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 1215811 (2022) https://doi.org/10.1117/12.2626908
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China

Abstract

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.

Citation Download Citation

Ming Xie "Power system terminal continuous trust evaluation model based on fine-grained data flow analysis", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 1215811 (2 March 2022); https://doi.org/10.1117/12.2626908

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