基于卷积神经网络的变电站数据处理平台攻击检测技术  

Attack Detection Technology of Substation Data Processing Platform Based on Convolutional Neural Network

作　　者：赵国欣 胡青璞 ZHAO Guoxin;HU Qingpu(chool of Electrical Engineering,Yellow River Conservancy Technical Institute,Kaifeng 475000,China)

机构地区：[1]黄河水利职业技术学院电气工程学院,河南开封475000

出　　处：《长江信息通信》2024年第8期57-59,共3页Changjiang Information & Communications

摘　　要：卷积神经网络是一种深度学习技术,根据模拟人类大脑处理信息的方式来分析和处理数据,特别适合于处理有着高复杂性和大数据量的问题,如变电站数据处理平台所面临的攻击检测。文章详细阐述了基于卷积神经网络的变电站数据处理平台攻击检测技术,首先介绍了变电站数据处理平台的系统工作原理,随后详细描述了该技术的系统架构、维保平台优化方案、监督攻击检测方法,根据系统测试验证了所提方法的有效性,展示了其在提高变电站数据安全和降低潜在攻击风险方面的巨大潜力。Convolutional neural network is a deep learning technology that analyzes and processes data according to the way the human brain processes information.It is especially suitable for dealing with problems with high complexity and large amount of data,such as the attack detection faced by the substation data processing platform.In this paper,the attack detcction tcchnology of substation data procssing platform based on convolutional neural network is claborated.First,the system working principle of substation data procssing platform is introduced,and then the system architecture,maintenance platform optimization scheme and supervision attack detection method of this technology are described in detail.The effectiveness of the proposed method is verified by system testing.Demonstrated its great potential to improve data security in substations and reduce the risk of potential attacks.

关 键 词：数据处理 卷积神经网络 变电站 攻击检测技术 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]