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Malware analysis method using visualization of binary files

Authors
Han, KyoungsooLim, Jae HyunIm, Eul Gyu
Issue Date
Oct-2013
Publisher
Association for Computing Machinary, Inc.
Keywords
malware analysis; malware detection; malware similarity; malware visualization
Citation
Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013, pp.317 - 321
Indexed
SCOPUS
Journal Title
Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013
Start Page
317
End Page
321
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/161780
DOI
10.1145/2513228.2513294
ISSN
0000-0000
Abstract
Malware authors have been generating and disseminating malware variants through various ways, such as reusing modules or using automated malware generation tools. With the help of the malware generation techniques, the number of malware keeps increasing every year. Therefore, new malware analysis techniques are needed to reduce malware analysis overheads. Recently several malware visualization methods were proposed to help malware analysts. In this paper, we proposed a novel method to visually analyze malware by transforming malware binary information into image matrices. Our experimental results show that the image matrices of malware can effectively classify malware families.
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서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles

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