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http://dx.doi.org/10.3745/KTCCS.2022.11.7.225

A Study on the Image-Based Malware Classification System that Combines Image Preprocessing and Ensemble Techniques for High Accuracy  

Kim, Hae Soo (한경대학교 컴퓨터응용수학부)
Kim, Mi Hui (한경대학교 컴퓨터응용수학부 컴퓨터시스템연구소)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.11, no.7, 2022 , pp. 225-232 More about this Journal
Abstract
Recent development in information and communication technology has been beneficial to many, but at the same time, malicious attack attempts are also increasing through vulnerabilities in new programs. Among malicious attacks, malware operate in various ways and is distributed to people in new ways every time, and to solve this malware, it is necessary to quickly analyze and provide defense techniques. If new malware can be classified into the same type of malware, malware has similar behavioral characteristics, so they can provide defense techniques for new malware using analyzed malware. Therefore, there is a need for a solution to this because the method of accurately and quickly classifying malware and the number of data may not be uniform for each family of analyzed malware. This paper proposes a system that combines image preprocessing and ensemble techniques to increase accuracy in imbalanced data.
Keywords
Malware; Deep Learning; Image Preprocessing; Ensemble;
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