摘要
智能变电站5G通信网络的数据量较大,会在一定程度上影响入侵节点特征分析,导致监测准确性低。文章提出5G通信网络节点入侵监测技术,通过分析监视节点数据,确定入侵通信网络异常特征函数,进而提取出异常特征的多特征相关性,实现入侵状态判定。测试显示,该方法的准确性高,监测到的入侵样本数量基本与实际输入的入侵样本数量一致,显著优于对照组,具备较好的实际应用价值,有助于提升智能变电站5G通信网络的安全性和稳定性。
The large amount of data in the 5G communication network of smart substation will affect the analysis of intrusion node characteristics to a certain extent,resulting in low monitoring accuracy.In this paper,the intrusion monitoring technology of 5G communication network nodes is proposed.By analyzing the data of monitoring nodes,the abnormal feature function of the intrusion communication network is determined,and then the multi-feature correlation of abnormal features is extracted to realize the intrusion state judgment.The test shows that the method has high accuracy,and the number of monitored intrusion samples is basically the same as the number of actually input intrusion samples,which is significantly better than that of the control group.It has good practical application value and is helpful to improve the security and stability of the 5G communication network of smart substation.
作者
梁欢
冯欢
LIANG Huan;FENG Huan(State Grid Ningxia Electric Power Co.,Ltd.,Zhongwei Power Supply Company,Zhongwei 755000,China)
出处
《通信电源技术》
2024年第21期165-167,共3页
Telecom Power Technology
关键词
智能变电站
5G通信
网络节点
入侵状态
网络信息安全
smart substation
5G communication
network node
intrusion status
network information security
