Advanced malware variant detection algorithm using structural characteristic of executable file

Authors:
Donghwi Shin;Kwangwoo Lee;Dongho Won
Affiliations:
Information Security Group, School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, Korea;Information Security Group, School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, Korea;Information Security Group, School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, Korea
Venue:
FGIT'11 Proceedings of the Third international conference on Future Generation Information Technology
Year:
2011

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Abstract

The malware is not the strange word. As much again the threat and number of malware is raising. However we and vendors do not arrange these malwares. They store these malware. The reason is the number is so many and the detail analysis is impossible. Therefore some researchers or vendor implemented the behavior based analysis system. However, these systems just analyze malware and do not arrangement. Although there are some arrangement or detection algorithms, there are just results of paper and are not implemented. In this paper, we propose the more available algorithm. The proposed algorithm is the updated version of the CFG (Control Flow Graph) based algorithm.