基于GAElman算法模型的电力信息网络安全态势评估  

Power Information Network Security Situation Assessment Based on GAElman Algorithm Model

作　　者：薛晓慧 马晓琴 薛峪峰 孙妍 李婧娇 Xue Xiaohui;Ma Xiaoqin;Xue Yufeng;Sun Yan;Li Jingjiao(State Grid Qinghai Electric Power Co.,Ltd.,Xining Qinghai 810000,China;Information&Communication Branch,State Grid Qinghai Electric Power Co.,Ltd.,Xining Qinghai 810000,China;School of Electric Power Engineering,Nanjing Institute of Technology,Nanjing Jiangsu 210000,China)

机构地区：[1]国网青海省电力公司,青海西宁810000 [2]国网青海省电力公司信息通信公司,青海西宁810000 [3]南京工程学院电力工程学院,江苏南京210000

出　　处：《电气自动化》2024年第1期78-82,共5页Electrical Automation

摘　　要：为了提高电力信息网络安全态势评估能力,提出了Elman神经网络模型。在模型中将遗传算法引入Elman算法,并通过主动式和被动式相结合的采集技术对电力信息网络进行数据收集,将各个数据源的原始数据进行综合分析和处理。在具体应用中,通过控制芯片为STM32F429ZET6单片机的ARM32位Cortex TM-M4处理器内核,大大提高了电力信息网络安全态势评估控制能力。试验结果显示,研究方法的评估准确率最高为97.9%,为下一步技术的研究奠定了基础。In order to improve the ability of power information network security situation assessment,an Elman neural network model was proposed.In the model,genetic algorithm was introduced into the Elman algorithm,and data collection in the power information network was realized through a combination of active and passive collection techniques.The original data from each data source was comprehensively analyzed and processed.In specific applications,the ARM32 bit Cortex TM-M4 processor core with STM32F429ZET6 microcontroller as the control chip greatly improved the control ability of power information network security situation assessment.The experimental results show that the evaluation accuracy of this research method is up to 97.9%,which lays the foundation for the next step of technology research.

关 键 词：网络安全 态势评估 搜索神经网络模型 控制芯片 评估力 ELMAN神经网络 

分 类 号：TP37[自动化与计算机技术—计算机系统结构] TM93[自动化与计算机技术—计算机科学与技术]