Malware Packing Analysis Based on Convolutional Neural Network with 2-Dimension Static Feature Set 


Vol. 43,  No. 12, pp. 2089-2099, Dec.  2018
10.7840/kics.2018.43.12.2089


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  Abstract

Along with the recent explosion of malicious code, malicious code is becoming intelligent / advanced. One of these trends is that most malicious code apply to the packing technique makes analysis difficult. In the case of malicious code automated analysis systems adopting static analysis with low system performance constraints in order to cope with a large amount of malicious codes in real time, analysis performance is deteriorated due to such a packing technique. Various packer identification studies have been carried out. However, due to the complicated mechanism, it is difficult cope with a large number of malicious codes. In this paper, we propose a lightweight packing analysis system that can simplify and lightly construct while maintaining analytical performance. This is possible by linking a static analysis technique with high-speed analysis capability to a high-dimensional feature combination and Convolutional Neural Network with excellent performance similar group classification. The results of this study can be operated as an independent module and it will be possible to operate as a pre-filter system that identifies the packer group in advance by linking with existing antivirus or automated malicious code analysis system through continuous research.

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  Cite this article

[IEEE Style]

J. Hwang and T. Lee, "Malware Packing Analysis Based on Convolutional Neural Network with 2-Dimension Static Feature Set," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 12, pp. 2089-2099, 2018. DOI: 10.7840/kics.2018.43.12.2089.

[ACM Style]

Jun-ho Hwang and Tae-jin Lee. 2018. Malware Packing Analysis Based on Convolutional Neural Network with 2-Dimension Static Feature Set. The Journal of Korean Institute of Communications and Information Sciences, 43, 12, (2018), 2089-2099. DOI: 10.7840/kics.2018.43.12.2089.

[KICS Style]

Jun-ho Hwang and Tae-jin Lee, "Malware Packing Analysis Based on Convolutional Neural Network with 2-Dimension Static Feature Set," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 12, pp. 2089-2099, 12. 2018. (https://doi.org/10.7840/kics.2018.43.12.2089)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880