信息工程大学学报2025，Vol.26Issue(1)：57-63,82,8.DOI:10.3969/j.issn.1671-0673.2025.01.009
基于多分类器的电力监控系统未知威胁检测方法
Unknown Threat Detection Method for Power Monitoring System Based on Multiple Classifiers
苏扬 1曹扬 1郭舒扬 1韩晓鹏 2张伟丽3
作者信息
- 1. 中国南方电网 电力调度控制中心,广东 广州 510663
- 2. 紫金山实验室 内生安全研究中心,江苏 南京 211111
- 3. 信息工程大学,河南 郑州 450001
- 折叠
摘要
Abstract
The traditional network defense technologies,which rely on prior knowledge,are thus lim-ited in effectiveness against complex,covert,and unknown threats.An unknown threat detection method is proposed,based on endogenous security theory and the dynamic heterogeneous redundancy(DHR)architecture,to improve the accuracy of anomaly detection in traffic within power monitoring systems.In this method,the advantages of multiple classifiers are integrated and a dynamically hetero-geneous and redundant learning framework is adopted.Ensemble learning,discriminative models,and other heterogeneous learning techniques are leveraged to enhance the robustness and accuracy of the model.The core technology involved consists of multi-classifier voting and feedback mechanisms,which are utilized to iteratively optimize and adjust sample distribution for continuous improvement in detection performance.The advantages of the method include reducing the generalization issue of single models,mitigating the risk of falling into local minima,and expanding the representation space to enhance adaptability.Experimental results showed that high accuracy in detecting unknown threats in power monitoring systems is achieved by using the proposed method.关键词
电力监控系统/内生安全/未知威胁检测/异常检测/态势感知Key words
power monitoring system/endogenous security/unknown threat detection/anomaly de-tection/situation awareness分类
信息技术与安全科学引用本文复制引用
苏扬,曹扬,郭舒扬,韩晓鹏,张伟丽..基于多分类器的电力监控系统未知威胁检测方法[J].信息工程大学学报,2025,26(1):57-63,82,8.
