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


KIPS Transactions on Computer and Communication Systems, Vol. 11, No. 7, pp. 225-232, Jul. 2022
https://doi.org/10.3745/KTCCS.2022.11.7.225,   PDF Download:
Keywords: Malware, Deep Learning, Image Preprocessing, Ensemble
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.


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Cite this article
[IEEE Style]
K. H. Soo and K. M. Hui, "A Study on the Image-Based Malware Classification System that Combines Image Preprocessing and Ensemble Techniques for High Accuracy," KIPS Transactions on Computer and Communication Systems, vol. 11, no. 7, pp. 225-232, 2022. DOI: https://doi.org/10.3745/KTCCS.2022.11.7.225.

[ACM Style]
Kim Hae Soo and Kim Mi Hui. 2022. A Study on the Image-Based Malware Classification System that Combines Image Preprocessing and Ensemble Techniques for High Accuracy. KIPS Transactions on Computer and Communication Systems, 11, 7, (2022), 225-232. DOI: https://doi.org/10.3745/KTCCS.2022.11.7.225.