摘要
本研究基于深度学习的电力系统无线通信网络漏洞检测方面,先介绍了电力系统和无线通信网络的基本情况,然后分析了该网络存在的安全漏洞,随后提出了利用深度学习技术来检测这些漏洞的方法.检测网络安全漏洞的步骤方法具体分为数据收集、数据预处理、模型选择和设计、模型训练、评估以及漏洞检测与修复等.在此基础上,文章详细说明了深度学习在网络安全检测中的技术优势和关键作用.通过本研究,发现深度学习技术可以有效识别和解决电力系统无线通信网络的安全漏洞问题.
Abstract
Based on deep learning,this study first introduces the basic situation of the power system and the wireless communication network of the power system,and then analyzes the security vulnerabilities of the network.Then,a method of using deep learning technology to detect these vulnerabilities is proposed,and the steps and methods of detecting network security vulnerabilities are divided into data collection,data preprocessing,model selection and design,model training,evaluation,and vulnerability detection and repair.On this basis,this paper elaborates on the technical advantages and key role of deep learning in network security detection.Through this study,it is believed that deep learning technology can more effectively identify and solve the security problems of wireless communication networks in power systems.
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