计算技术与自动化2025，Vol.44Issue(3)：24-29,6.DOI:10.16339/j.cnki.jsjsyzdh.202503005
基于动态克隆选择算法和SSA算法的供电信息监控数据中心入侵检测方法
Intrusion Detection Method for Power Supply Information Monitoring Data Center Based on Dynamic Clone Selection Algorithm and SSA Algorithm
王雨 1王庆贤 1杨麒渲 2张超 2华梅1
作者信息
- 1. 国家电网有限公司客户服务中心,天津 300300
- 2. 北京中电普华信息技术有限公司,北京 100031
- 折叠
摘要
Abstract
Due to the lack of sparse representation of data features,the false alarm rate of detection results is high,and the detection effect is not ideal.To this end,a power supply information monitoring data center intrusion detection method based on dynamic clone selection algorithm and sparrow search algorithm(SSA)algorithm is proposed.Based on the charac-teristic distribution characteristics of intrusion data in the power supply information monitoring data center,a dynamic clo-ning algorithm is used to construct an adjustment extractor,which converts the dynamic features of intrusion data into nu-merical features,completes intrusion feature recognition,enhances the features of intrusion data in combination with rough set theory,and introduces the Lande factor to map intrusion data features to an equal dimensional space to obtain a sparse expression of data features.Based on this,using extreme learning institutions to build intrusion detection models,and using SSA to obtain internal parameters of the model,an optimized detection model is obtained.Intrusion data detection is a-chieved by calculating the distance between the test data sample and the detection center.The experimental results show that the false alarm rate of the detection results output by the proposed method is low,and the detection performance is good.关键词
动态克隆选择算法/SSA算法/供电信息监控数据中心/入侵数据Key words
dynamic clone selection algorithm/SSA algorithm/power supply information monitoring data center/intru-sion data分类
信息技术与安全科学引用本文复制引用
王雨,王庆贤,杨麒渲,张超,华梅..基于动态克隆选择算法和SSA算法的供电信息监控数据中心入侵检测方法[J].计算技术与自动化,2025,44(3):24-29,6.
