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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Identification of Peer-to-Peer VoIP Sessions Using Entropy and Codec Properties
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Identification of Peer-to-Peer VoIP Sessions Using Entropy and Codec Properties

机译：使用熵和编解码器属性识别对等VoIP会话

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摘要

Voice over Internet Protocol (VoIP) applications based on peer-to-peer (P2P) communications have been experiencing considerable growth in terms of number of users. To overcome filtering policies or protect the privacy of their users, most of these applications implement mechanisms such as protocol obfuscation or payload encryption that avoid the inspection of their traffic, making it difficult to identify its nature. The incapacity to determine the application that is responsible for a certain flow raises challenges for the effective management of the network. In this paper, a new method for the identification of VoIP sessions is presented. The proposed mechanism classifies the flows, in real-time, based on the speech codec used in the session. To make the classification lightweight, the behavioral signatures for each analyzed codec were created using only the lengths of the packets. Unlike most previous approaches, the classifier does not use the lengths of the packets individually. Instead, it explores their level of heterogeneity in real time, using entropy to emphasize such feature. The results of the performance evaluation show that the proposed method is able to identify VoIP sessions accurately and simultaneously recognize the used speech codec.
机译：基于对等（P2P）通信的Internet协议语音（VoIP）应用程序在用户数量方面已经历了可观的增长。为了克服过滤策略或保护其用户的隐私，这些应用程序中的大多数实现了诸如协议混淆或有效负载加密之类的机制，这些机制避免了对其流量的检查，从而使其难以识别其性质。无法确定负责某个流程的应用程序对网络的有效管理提出了挑战。本文提出了一种识别VoIP会话的新方法。所提出的机制基于会话中使用的语音编解码器实时对流进行分类。为了使分类轻巧，仅使用数据包的长度为每个分析的编解码器创建了行为签名。与大多数以前的方法不同，分类器不会单独使用数据包的长度。取而代之的是，它使用熵来强调此类特征，从而实时探索其异质性水平。性能评估结果表明，该方法能够准确识别VoIP会话并同时识别使用的语音编解码器。

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