%0 Journal Article
%T Survey of Research on Anomaly Detection of Wavelet Analysis Based on Network Traffic<br>基于网络流量小波分析的异常检测研究
%A XIAO Zheng-hong
%A PAN Mei-sen
%A YIN Hao
%A <br>肖政宏
%A 潘梅森
%A 尹浩
%J 计算机应用研究
%D 2007
%I 
%X 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.
%K Network Traffic
%K Wavelets Analysis
%K Self-similarity
%K Hurst Parameter
%K Anomaly Detection<br>网络流量
%K 小波分析
%K 自相似性
%K Hurst参数
%K 异常检测
%K 网络流量
%K 小波分析
%K 异常行为
%K 检测研究
%K Network
%K Traffic
%K Based
%K Wavelet
%K Analysis
%K Anomaly
%K Detection
%K Research
%K 位置
%K 发生
%K 流量攻击
%K 突发性
%K 存在
%K 发现
%K 测试结果
%K DARPA
%K 比较
%K 变化
%K 特征参数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=343459AF1736CA695C8AFCC83ADA35C9&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=0B39A22176CE99FB&sid=BF112261B65CB9C9&eid=DFEE4E8C33C95CEF&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=3&reference_num=14