Malware classification method via binary content comparison
- Authors
- Kim, Taeguen; Kang, Boojoong; Im, Eul Gyu
- Issue Date
- May-2013
- Publisher
- International Information Institute Ltd.
- Keywords
- Binary analysis; Malware classification; Malware detection; Malware similarity; Static analysis
- Citation
- Information (Japan), v.16, no.8:00 AM, pp.5773 - 5788
- Indexed
- SCIE
SCOPUS
- Journal Title
- Information (Japan)
- Volume
- 16
- Number
- 8:00 AM
- Start Page
- 5773
- End Page
- 5788
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/162821
- ISSN
- 1343-4500
- Abstract
- With the wide spread uses of the Internet, the number of Internet attacks keeps increasing, and malware is the main cause of most Internet attacks. Malware is used by attackers to infect normal users' computers and to acquire private information as well as to attack other machines. The number of new malware and variants of malware is increasing every year because the automated tools allow attackers to generate the new malware or their variants easily. Therefore, performance improvement of the malware analysis is critical to prevent malware from spreading rapidly and to mitigate damages to users. In this paper, we proposed a new malware classification method by analyzing similarities of malware. Our method analyzes a small part of malware to reduce analysis overheads, and experimental results showed that our approach can effectively classify malware families.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - 서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.