Presentation 2005-04-21
Classifying Flow Characteristics using Naive Bayesian Classifier
Tatsuya MORI, Ryoichi KAWAHARA, Noriaki KAMIYAMA,
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Abstract(in English) The statistics of flow, which is an unit of traffic produced by each user or application, gives us a meaningful insight for making practical network management. That is, if we rapidly knew the anomaly flows that might significantly affect the network performance, then we can immediately make an adequate action aganist such flows to protect our networks. It also allows us to make nice controlling scheams or effective troubleshooting. This paper delvelops new method to establish such an objective, using Naive Bayesian Classifier. Using the learned statistics, which can be obtained from measurement, the method probabilisticly estimate the class to which newly arrived flows may belong. Since the method does not maintain per-flow statistics, it has strong scalability. We evaluate the accuracy of the method, using measured packet traces.
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Keyword(in English) measurement / flow / anomaly / Naive Bayesian Classifier
Paper # NS2005-3
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Committee NS
Conference Date 2005/4/14(1days)
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Registration To Network Systems(NS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Classifying Flow Characteristics using Naive Bayesian Classifier
Sub Title (in English)
Keyword(1) measurement
Keyword(2) flow
Keyword(3) anomaly
Keyword(4) Naive Bayesian Classifier
1st Author's Name Tatsuya MORI
1st Author's Affiliation NTT Service Integration Laboratories()
2nd Author's Name Ryoichi KAWAHARA
2nd Author's Affiliation NTT Service Integration Laboratories
3rd Author's Name Noriaki KAMIYAMA
3rd Author's Affiliation NTT Service Integration Laboratories
Date 2005-04-21
Paper # NS2005-3
Volume (vol) vol.105
Number (no) 12
Page pp.pp.-
#Pages 4
Date of Issue