Presentation 2007-01-19
Analysis and Visualization of Network IDS Data Using Machine Learning
Hayato OHBA, JungSuk SONG, Hiroki TAKAKURA, Yasuo OKABE,
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Abstract(in English) In this paper, we clarify the differences between both datasets by using the log data of an IDS deployed in Kyoto University and propose novel visualizing method based on machine learning. One of the major problems of IDS is a huge amount of false positive rate. As a mater of face, various data mining and visualizing techniques have been proposed to overcome the problem. KDDCup'99, presented in 1999 is used even until now. However, the dataset is not able to handle current intrusions.
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Keyword(in English) IDS / Visualization / KDDCup'99 / LBG algorithm
Paper # IA2006-36
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Committee IA
Conference Date 2007/1/11(1days)
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Registration To Internet Architecture(IA)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Analysis and Visualization of Network IDS Data Using Machine Learning
Sub Title (in English)
Keyword(1) IDS
Keyword(2) Visualization
Keyword(3) KDDCup'99
Keyword(4) LBG algorithm
1st Author's Name Hayato OHBA
1st Author's Affiliation Graduate School of informatics, Kyoto University()
2nd Author's Name JungSuk SONG
2nd Author's Affiliation Graduate School of informatics, Kyoto University
3rd Author's Name Hiroki TAKAKURA
3rd Author's Affiliation Academic Center for Computing and Media Studies, Kyoto University
4th Author's Name Yasuo OKABE
4th Author's Affiliation Academic Center for Computing and Media Studies, Kyoto University
Date 2007-01-19
Paper # IA2006-36
Volume (vol) vol.106
Number (no) 465
Page pp.pp.-
#Pages 6
Date of Issue