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.
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Dengfeng ZHANG, Naoshi NAKAYA, Yuuji KOUI, Hitoaki YOSHIDA, "An Automatic Unpacking Method for Computer Virus Effective in the Virus Filter Based on Paul Graham's Bayesian Theorem" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 4, pp. 1119-1127, April 2009, doi: 10.1587/transcom.E92.B.1119.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.1119/_p
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@ARTICLE{e92-b_4_1119,
author={Dengfeng ZHANG, Naoshi NAKAYA, Yuuji KOUI, Hitoaki YOSHIDA, },
journal={IEICE TRANSACTIONS on Communications},
title={An Automatic Unpacking Method for Computer Virus Effective in the Virus Filter Based on Paul Graham's Bayesian Theorem},
year={2009},
volume={E92-B},
number={4},
pages={1119-1127},
abstract={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.},
keywords={},
doi={10.1587/transcom.E92.B.1119},
ISSN={1745-1345},
month={April},}
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TY - JOUR
TI - An Automatic Unpacking Method for Computer Virus Effective in the Virus Filter Based on Paul Graham's Bayesian Theorem
T2 - IEICE TRANSACTIONS on Communications
SP - 1119
EP - 1127
AU - Dengfeng ZHANG
AU - Naoshi NAKAYA
AU - Yuuji KOUI
AU - Hitoaki YOSHIDA
PY - 2009
DO - 10.1587/transcom.E92.B.1119
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2009
AB - 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.
ER -