Rapid and generalized identification of packetized voice traffic flows

P. Branch, J. But
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引用次数: 15

Abstract

In this paper we describe the construction and performance of classifiers able to identify Variable Rate VoIP traffic flows rapidly, reliably and independently of the application version that generated it. We show that features calculated on short sequences of packets extracted from the flow (sub-flows) are sufficient to identify VoIP flows with Recall of 99% and Precision of 90%. The features we used are based on mean packet length, autocorrelation and the ratio of data transmitted in either direction of a bi-directional flow. Even though the codecs we use to generate VoIP traffic are quite different, we show that by using selected features that capture the nature of variable bit rate voice traffic, a classifier trained on traffic generated by one version of VoIP can reliably recognize traffic generated by another version.
分组话音流量的快速和广义识别
在本文中,我们描述了分类器的结构和性能,这些分类器能够快速、可靠地识别可变速率VoIP流量,并且独立于生成它的应用程序版本。我们表明,在从流(子流)中提取的数据包的短序列上计算的特征足以识别具有99%召回率和90%精度的VoIP流。我们使用的特征是基于平均数据包长度,自相关性和双向流中任意方向传输的数据比率。尽管我们用于生成VoIP流量的编解码器是完全不同的,但我们表明,通过使用捕获可变比特率语音流量性质的选定特征,对一个版本的VoIP生成的流量进行训练的分类器可以可靠地识别由另一个版本生成的流量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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