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01233 am a22001813u 4500 |
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|a Bassi, J. S.
|e author
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|a Ru, L. H.
|e author
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|a Ismail, I.
|e author
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|a Khammas, B. M.
|e author
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|a Marsono, M. N.
|e author
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|a Online peer-to-peer traffic identification based on complex events processing of traffic event signatures
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|b Penerbit UTM Press,
|c 2016.
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|z Get fulltext
|u http://eprints.utm.my/id/eprint/70107/1/JosephStephenBassi2016_OnlinePeertoPeerTrafficIdentificationBased.pdf
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|a Peer-to-Peer (P2P) applications are bandwidth-heavy and lead to network congestion. The masquerading nature of P2P traffic makes conventional methods of its identification futile. In order to manage and control P2P traffic efficiently preferably in the network, it is necessary to identify such traffic online and accurately. This paper proposes a technique for online P2P identification based on traffic events signatures. The experimental results show that it is able to identify P2P traffic on the fly with an accuracy of 97.7%, precision of 98% and recall of 99.2%.
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|a en
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|a TK Electrical engineering. Electronics Nuclear engineering
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