摘要
针对流量识别方法受到服务端口、协议签名、流量加密等限制的问题,提出一种基于多尺度小波谱的流量识别方法。利用离散小波变换对原始网络流量进行多尺度分解,分别计算不同尺度下的小波谱,使用K-means算法对这些小波谱进行聚类分析,由此实现网络流量的识别。实验结果表明,该方法具有较高的识别准确率。
Aiming at the problem of current traffic identification method limited by service port,protocol signatures and traffic encryption,this paper proposes a new traffic identification method based on multi-scale wavelet spectrum.The new method is able to achieve the identification of different network traffic by performing clustering analysis of K-means algorithm over the different scales wavelet spectrum coefficients that are inferred from the raw traffic by using Discrete Wavelet Transform（DWT）.Experimental result shows that it has accurate identification results.
出处
《计算机工程》
CAS
CSCD
2012年第12期72-74,78,共4页
Computer Engineering
基金
国家自然科学基金资助重点项目(60933011)
国家自然科学基金资助项目(60873248)
关键词
流量识别
流量加密
离散小波变换
多尺度分解
小波谱
聚类分析
traffic identification
traffic encryption
Discrete Wavelet Transform（DWT）
multi-scale decomposition
wavelet spectrum
clustering analysis
