Presentation | 2010-11-24 高精度なネットワーク侵入検知システムの構築(学生セッション,学生セッション,一般) Moriteru ISHIDA, Hiroki TAKAKURA, Yasuo OKABE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Intrusion detection systems(IDSs) are important equipments for network security. Recently, there's been an emerging research on them and especially several studies have focused on anomaly based IDSs using unsupervised machine learning techniques. However past studies still haven't overcome two problems, i.e., low detection rate and high false positive rate. In addition, there is a problem that past reserches haven' t been evaluated with real traffic data. In order to solve them, we propose an application of the clustering algorithm based on OptiGrid to IDS and an improvement of the existing cluster-labeling method. We also evaluate our system with both KDDCUP1999 data and real traffic data collected by honeypots in Kyoto University. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | intrusion detection system / IDS / anomaly detection / clustering / OptiGrid |
Paper # | IA2010-56 |
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Committee | IA |
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Conference Date | 2010/11/17(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Internet Architecture(IA) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
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Keyword(1) | intrusion detection system |
Keyword(2) | IDS |
Keyword(3) | anomaly detection |
Keyword(4) | clustering |
Keyword(5) | OptiGrid |
1st Author's Name | Moriteru ISHIDA |
1st Author's Affiliation | Guraduate School of Informatics, Kyoto University() |
2nd Author's Name | Hiroki TAKAKURA |
2nd Author's Affiliation | Information Technology Center, Nagoya University |
3rd Author's Name | Yasuo OKABE |
3rd Author's Affiliation | Academic Center for Computing and Media Studies, Kyoto University |
Date | 2010-11-24 |
Paper # | IA2010-56 |
Volume (vol) | vol.110 |
Number (no) | 304 |
Page | pp.pp.- |
#Pages | 6 |
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