Internet Traffic Classification Using Multifractal Analysis Approach

机译：基于多重分形分析的互联网流量分类

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In this paper, we present a traffic classifier based on the theory of multifractal network traffic. We use precisely the concept of multiplicative binomial cascades to get a feature vector to be used in the classification scheme. This vector is obtained by the multiplier variances of the multiplicative cascade traffic view. We analyze the performance of the technique proposed by a popular ML Software-based and the results showed viability classification rates of traffic over 90%.

机译：在本文中，我们提出了一种基于多重分形网络流量理论的流量分类器。我们正好使用乘法二项式级联的概念来获取要在分类方案中使用的特征向量。该矢量是通过可乘级联流量视图的乘方方差获得的。我们分析了基于流行的ML Software提出的技术的性能，结果显示流量的可行性分类率超过90％。

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《》|2012年|p.38-42|共5页
会议地点 Orlando FL(US);Orlando FL(US);Orlando FL(US);Orlando FL(US)
作者
Yulios Zavala; Jeferson Wilian de Godoy Stenico; Lee Luan Ling;
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作者单位

School of Electrical and Computer Engineering State University of Campinas - UNICAMP PO Box 6101-13.083-970, Campinas, SP, Brazil;

School of Electrical and Computer Engineering State University of Campinas - UNICAMP PO Box 6101-13.083-970, Campinas, SP, Brazil;

School of Electrical and Computer Engineering State University of Campinas - UNICAMP PO Box 6101-13.083-970, Campinas, SP, Brazil;

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原文格式 PDF
正文语种 eng
中图分类通信;计算机网络;计算机网络;
关键词
network traffic; traffic classification; multifractal analysis; multiplicative cascade;

机译：网络流量；交通分类;分形分析;乘法级联;

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Internet Traffic Classification Using Multifractal Analysis Approach

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