Presentation 2002/3/13
Studies on the Intrusion Detection System using Modular Neural Networks
Hiroshi SHIRATSUCHI, Kazuki SHIMABUKURO, Naoki HIGA,
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Abstract(in English) This report studies that the Intrusion Detection System(IDS) using modular neural networks(MNN) improves the unknown attacks detection. It is proposed that the learning method for composing the personal profile at the normally situation on each module of the MNN. Each UNIX's commands with packet capturing are encoded by the characteristic attributes. These attributes are selected from among the behavior, which can guess the intruder, for example execute capability, using network ports, important keywords matching. From the simulation, using the actual network packet, it is shown that the proposed personal discernment system is detected to the unknown users.
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Keyword(in English) IDS / Personal profile / modular neural networks
Paper # NC2001-225
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Committee NC
Conference Date 2002/3/13(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Studies on the Intrusion Detection System using Modular Neural Networks
Sub Title (in English)
Keyword(1) IDS
Keyword(2) Personal profile
Keyword(3) modular neural networks
1st Author's Name Hiroshi SHIRATSUCHI
1st Author's Affiliation Faculty of Engineering, University of the Ryukyus()
2nd Author's Name Kazuki SHIMABUKURO
2nd Author's Affiliation Faculty of Engineering, University of the Ryukyus
3rd Author's Name Naoki HIGA
3rd Author's Affiliation Faculty of Engineering, University of the Ryukyus
Date 2002/3/13
Paper # NC2001-225
Volume (vol) vol.101
Number (no) 737
Page pp.pp.-
#Pages 6
Date of Issue