Presentation 2008-07-25
Detection of Unknown Computer Virus Variants Based on Computer Behavior
Haruka MIMORI, Koki ABE,
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Abstract(in English) We observed the behavior of computer viruses by monitoring the behavior of computers infected by the mass-mailing viruses. We employed machine learning methods to learn the behaviors of known virus variants to identify unknown variants. The learning results using eight kinds of viruses each with three variants revealed that the methods can correctly identify unknown virus variants with an accuracy of more than 80%. It was also found that the accuracy of identification differs among different kinds of viruses, but the accuracy of identifying virus variants discovered close in time tends to be high.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Unknown viruses / variants / data mining
Paper # ISEC2008-35
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Committee ISEC
Conference Date 2008/7/17(1days)
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Paper Information
Registration To Information Security (ISEC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Detection of Unknown Computer Virus Variants Based on Computer Behavior
Sub Title (in English)
Keyword(1) Unknown viruses
Keyword(2) variants
Keyword(3) data mining
1st Author's Name Haruka MIMORI
1st Author's Affiliation Department of Computer Science, he University of Electro-Communications()
2nd Author's Name Koki ABE
2nd Author's Affiliation Department of Computer Science, he University of Electro-Communications
Date 2008-07-25
Paper # ISEC2008-35
Volume (vol) vol.108
Number (no) 162
Page pp.pp.-
#Pages 7
Date of Issue