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Similarity Calculation Method for User-Define Functions to Detect Malware Variants

Title
Similarity Calculation Method for User-Define Functions to Detect Malware Variants
Author
임을규
Keywords
malware analysis; smith-waterman algorithm; static analysis
Issue Date
2014-10
Publisher
Association for Computing Machinery, Inc
Citation
Proceedings of the 2014 Research in Adaptive and Convergent Systems, RACS 2014. (Proceedings of the 2014 Research in Adaptive and Convergent Systems, RACS 2014, 5 October 2014, p.236-241
Abstract
The number of malware has sharply increased over years, and it caused various damages on computing systems and data. In this paper, we propose techniques to detect malware variants. Malware authors usually reuse malware modules when they generate new malware or malware variants. Therefore, malware variants have common code for some functions in their binary files. We focused on this common code in this research, and proposed the techniques to detect malware variants through similarity calculation of user-defined function. Since many malware variants evade malware detection system by transforming their static signatures, to cope with this problem, we applied pattern matching algorithms for DNA variations in Bioinformatics to similarity calculation of malware binary files. Since the pattern matching algorithm we used provides the local alignment function, small modification of functions can be overcome. Experimental results show that our proposed method can detect malware similarity and it is more resilient than other methods.
URI
https://dl.acm.org/citation.cfm?id=2664222http://hdl.handle.net/20.500.11754/56989
ISBN
978-1-4503-3060-2
DOI
10.1145/2663761.2664222
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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