摘要
采用子空间方法和主成分分析(PCA,Principal Components Analysis)对大规模网络流量异常检测进行研究,并以校园网为实验环境,应用子空间方法和PCA实现了网络流量异常检测。通过实验结果与小波分析结果的对比,证明了基于子空间方法的大规模网络流量异常检测是一种既简单又高效的方法。
Subspace method and PCA（Principal Components Analysis） are adopted in network-wide traffic anomaly detection research.In experiment environment of campus networks,the process of detecting network traffic anomalies is realized by applying subspace method and PCA.Through the comparison of the results from the experiment and wavelet analysis,it shows that network-wide traffic anomaly detection based on subspace method is more simple and effective.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第11期153-156,共4页
Computer Engineering and Applications
关键词
子空间方法
主成分分析
大规模网络流量
异常检测
subspace method
Principal Components Analysis （PCA）
network-wide traffic
anomaly detection
