Presentation | 2005-04-21 Classifying Flow Characteristics using Naive Bayesian Classifier Tatsuya MORI, Ryoichi KAWAHARA, Noriaki KAMIYAMA, |
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Abstract(in Japanese) | (See Japanese page) |
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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | measurement / flow / anomaly / Naive Bayesian Classifier |
Paper # | NS2005-3 |
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Committee | NS |
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Conference Date | 2005/4/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Network Systems(NS) |
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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 |
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