摘要
随着网络规模与复杂性增加,光纤通信网络面临严重的安全威胁,特别是恶意数据。为此,提出基于改进SVM的恶意数据自动检测方法。该方法先收集并预处理光纤通信数据,再构建改进SVM模型分类恶意与正常数据,最后实现光纤通信网络恶意数据的自动检测。实验证明,该自动检测方法能准确识别数据集中的恶意数据,有效应对网络威胁。
With the increase in network size and complexity,fiber optic communication networks are facing serious security threats,especially malicious data.Therefore,a malicious data automatic detection method based on improved SVM is proposed.This method first collects and preprocesses fiber optic communication data,then constructs an improved SVM model to classify malicious and normal data,and finally achieves automatic detection of malicious data in fiber optic communication networks.Experimental results have shown that this automatic detection method can accurately identify malicious data in the dataset and effectively respond to network threats.
作者
陈媛媛
王军
汪伟鸣
奚俊
温安平
CHEN Yuanyuan;WANG Jun;WANG Weiming;XI Jun;WEN Anping(Xuancheng Power Supply Company,State Grid Anhui Electric Power Co.,Ltd.,Xuancheng,Anhui 242000,China)
出处
《自动化应用》
2025年第4期260-261,265,共3页
Automation Application
关键词
数据自动检测
恶意数据
光纤通信网络
机器学习
改进SVM
网络规模
automatic data detection
malicious data
optical fiber communication network
machine learning
improved SVM
network size
