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An Automatic Unpacking Method for Computer Virus Effective in the Virus Filter Based on Paul Graham's Bayesian Theorem

Dengfeng ZHANG, Naoshi NAKAYA, Yuuji KOUI, Hitoaki YOSHIDA

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Summary :

Recently, the appearance frequency of computer virus variants has increased. Updates to virus information using the normal pattern matching method are increasingly unable to keep up with the speed at which viruses occur, since it takes time to extract the characteristic patterns for each virus. Therefore, a rapid, automatic virus detection algorithm using static code analysis is necessary. However, recent computer viruses are almost always compressed and obfuscated. It is difficult to determine the characteristics of the binary code from the obfuscated computer viruses. Therefore, this paper proposes a method that unpacks compressed computer viruses automatically independent of the compression format. The proposed method unpacks the common compression formats accurately 80% of the time, while unknown compression formats can also be unpacked. The proposed method is effective against unknown viruses by combining it with the existing known virus detection system like Paul Graham's Bayesian Virus Filter etc.

Publication
IEICE TRANSACTIONS on Communications Vol.E92-B No.4 pp.1119-1127
Publication Date
2009/04/01
Publicized
Online ISSN
1745-1345
DOI
10.1587/transcom.E92.B.1119
Type of Manuscript
Special Section PAPER (Special Section on Internet Technology and its Architecture for Ambient Information Systems)
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