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计算机工程 ›› 2012, Vol. 38 ›› Issue (12): 72-74. doi: 10.3969/j.issn.1000-3428.2012.12.021

• 网络与通信 • 上一篇    下一篇

一种基于小波谱的流量识别方法

时鸿涛 1,2,盖凌云 1 ,郭忠文 2   

  1. (1. 青岛农业大学网络管理中心,山东 青岛 266109;2. 中国海洋大学信息科学与工程学院,山东 青岛 266100)
  • 收稿日期:2011-08-22 出版日期:2012-06-20 发布日期:2012-06-20
  • 作者简介:时鸿涛(1981-),男,讲师、硕士,主研方向:网络安全;盖凌云,副教授、硕士;郭忠文,教授、博士生导师
  • 基金资助:

    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)

Traffic Identification Method Based on Wavelet Spectrum

SHI Hong-tao 1,2, GAI Ling-yun 1, GUO Zhong-wen 2   

  1. (1. Network Management Center, Qingdao Agricultural University, Qingdao 266109, China; 2. School of Information Science and Engineering, Ocean University of China, Qingdao 266100, China)
  • Received:2011-08-22 Online:2012-06-20 Published:2012-06-20

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。

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

Abstract: 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.

Key words: traffic identification, traffic encryption, Discrete Wavelet Transform(DWT), multi-scale decomposition, wavelet spectrum, clustering analysis

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