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Malware classification methods using API sequence characteristics

Title
Malware classification methods using API sequence characteristics
Author
임을규
Keywords
Malware; Malware analysis; Malware classification
Issue Date
2012-06
Publisher
Elsevier Science B.V
Citation
Lecture Notes in Electrical Engineering, 2012, 120, P.613-626
Abstract
Malware is generated to gain profits by attackers, and it infects many users' computers. As a result, attackers can acquire private information such as login IDs, passwords, e-mail addresses, cell-phone numbers and banking account numbers from infected machines. Moreover, infected machines can be used for other cyber-attacks such as DDoS attacks, spam e-mail transmissions, and so on. The number of new malware discovered every day is increasing continuously because the automated tools allow attackers to generate the new malware or their variants easily. Therefore, a rapid malware analysis method is required in order to mitigate the infection rate and secondary damage to users. In this paper, we proposed a malware variant classification method using sequential characteristics of API used, and described experiment results with some malware samples.
URI
https://link.springer.com/chapter/10.1007%2F978-94-007-2911-7_60http://hdl.handle.net/20.500.11754/67863
ISBN
978-940072910-0
ISSN
1876-1100
DOI
10.1007/978-94-007-2911-7_60
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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