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Detection methods for malware variant using API call related graphs

Authors
Han, Kyoung-SooKim, In-KyoungIm, Eul Gyu
Issue Date
Dec-2011
Publisher
Springer Verlag
Keywords
API call related graph; Malware detection; Malware variants
Citation
Lecture Notes in Electrical Engineering, v.120 LNEE, pp 607 - 611
Pages
5
Indexed
SCOPUS
Journal Title
Lecture Notes in Electrical Engineering
Volume
120 LNEE
Start Page
607
End Page
611
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/167009
DOI
10.1007/978-94-007-2911-7_59
ISSN
1876-1100
1876-1119
Abstract
Recently damages in users caused by malware have been increased. The malware presently propagated has been generated as variants by modifying it using various techniques and tools and that leads to significant increase in the number of malware. Thus, researches on various methods for detecting such malware have been conducted. In this paper, we proposed a method to detect malware variants through the measuring of similarity in control flow graphs related to API calls in malware.
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