2009 International Conference on Information Technology and Computer Science 2009
DOI: 10.1109/itcs.2009.257
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Abstract: These years, P2P applications have multiplied, evolved and take a big part of Internet traffic workload. Identifying the P2P traffic and understanding their behavior is an important field. Some port, payload and transport layer feature based methods were proposed. P2P traffic identification methods by examining user payload or well-defined port numbers no longer adapt to current P2P applications. In recent years, some scholars do researches on traffic classification by using Machine Learning. However, previous… Show more

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Cited by 9 publications
(5 citation statements)
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References 17 publications
(19 reference statements)
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“…Vector Machine for identification of P2P network traffic [5]. Their method identifies network traffic by analyzing packet length, remote hosts' discreteness, connection responded success rate and the ratio of IP and port at the host level without relying on the port numbers and packet payload, which are used as classification metrics.…”
Section: Feng Et Al Developed a New Methods That Is Based On Supportmentioning
confidence: 99%
“…Vector Machine for identification of P2P network traffic [5]. Their method identifies network traffic by analyzing packet length, remote hosts' discreteness, connection responded success rate and the ratio of IP and port at the host level without relying on the port numbers and packet payload, which are used as classification metrics.…”
Section: Feng Et Al Developed a New Methods That Is Based On Supportmentioning
confidence: 99%
“…To date, a common strategy is to collapse temporal data into aggregate values and neglect spatial structure [2,7,11,13,15,17,29,34,36,38,39,42,50,51]. This causes a loss of information as researchers remove streams of data that only occur once (e.g.…”
Section: Related Workmentioning
confidence: 99%
“…Many techniques have been proposed to identify and discourage this type of traffic within controlled environments (Douceur, 2002;Karagiannis et al, 2004;Constantinou and Mavrommatis, 2006;Davis et al, 2008;Gu et al, 2008a;2008b;Liu et al, 2009;Nagaraja et al, 2010;Yen and Reiter, 2010;Aviv and Haeberlen, 2011;Jian et al, 2012). Table 18 summarizes the P2P based botnet detection approaches.…”
Section: Botnet Detection Based On P2p Protocolsmentioning
confidence: 99%
“…Karagiannis et al (2004) evaluated signature-based searching, which is considered the first approach to measuring the efficiencies of different signature-based techniques in dealing with packet payload. Liu et al (2009) compared the P2P networks with traditional client/server architecture through application traffic. In their findings, every node acts as a server and a client simultaneously in a P2P network environment.…”
Section: Botnet Detection Based On P2p Protocolsmentioning
confidence: 99%