小波变换降噪技术在电力系统计算机网络安全管理中的应用

Application of Wavelet Transform Noise Reduction Technology in Electric Power System Computer Network Security Management

为进一步提升电力系统的安全防护能力,研究小波变换降噪技术在电力系统计算机网络安全管理中的应用。通过对网络流量数据进行小波分解、阈值处理、小波重构,实现网络流量的降噪和特征提取。结合机器学习算法,构建网络安全事件检测模型,以及时发现和应对各类安全威胁。为确定该技术的具体应用方案和效果,以某小型电力企业为例进行实践分析。实践表明,基于小波变换的网络安全管理方法可有效提升电力系统的安全防护能力。

In order to further improve the safety protection ability of power system,the application of wavelet transform noise reduction technology in computer network security management of power system is studied.Through wavelet decomposition,threshold processing and wavelet reconstruction of network traffic data,noise reduction and feature extraction of network traffic are realized.Combined with machine learning algorithms,the network security event detection model is built to timely discover and respond to various security threats.In order to determine the specific application scheme and effect of this technology,a small electric power enterprise is taken as an example for practical analysis.The practice shows that the network security management method based on wavelet transform can effectively improve the security protection ability of power system.