Malware analysis method using visualization of binary files
- Authors
- Han, Kyoungsoo; Lim, Jae Hyun; Im, 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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