Presentation 2003/1/31
A Security System for Anomaly Detection using Probabilistic Reasoning
Sachio TOISHIGAWA, Laurence ANTHONY, George V. LASHKIA,
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Abstract(in English) There are currently many kinds of security software. However, there are still few systems that can detect unauthorized actions by valid account holders or by camouflage. In this paper, we propose a new security system that can identify such actions by applying a novel variation of the Naive Bayes machine learning algorithm to anomaly detection. In order to classify a user's behavior, the system uses a set of command operations of a target user to construct a profile of the users 'normal' operations. Subsequent profiles of the same or a different user's operations are then compared and classified accordingly. Results from applying the system to user distinction and anomaly detection demonstrate that it can be an effective and practical approach in real-world contexts.
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Keyword(in English) Security / Network / Data Mining
Paper # IN2002-201,IA2002-57
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Committee IA
Conference Date 2003/1/31(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) A Security System for Anomaly Detection using Probabilistic Reasoning
Sub Title (in English)
Keyword(1) Security
Keyword(2) Network
Keyword(3) Data Mining
1st Author's Name Sachio TOISHIGAWA
1st Author's Affiliation Graduate School of Okayama University of Science,Okayama University of Science()
2nd Author's Name Laurence ANTHONY
2nd Author's Affiliation Okayama University of Science
3rd Author's Name George V. LASHKIA
3rd Author's Affiliation Okayama University of Science
Date 2003/1/31
Paper # IN2002-201,IA2002-57
Volume (vol) vol.102
Number (no) 636
Page pp.pp.-
#Pages 4
Date of Issue