Survey of Research on Anomaly Detection of Wavelet Analysis Based on Network Traffic
基于网络流量小波分析的异常检测研究

Network traffic is one of the key properties in LAN as well as WAN,by wavelet analysis,the complex traffic times series can be decomposed into different frequent components.Based on wavelet decomposed,the self-similar of traffic can be used to detect anomaly behavior of network,a method of detecting attacks based on the deviation of Hurst parameter is presented.The changes of Hurst parameter are analyzed and compared in different time scale.Result shows the proposed approach can detect the possible presence of not only an anomaly,but also its location on data set.