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A Smart System of Malware Detection Based on Artificial Immune Network and Deep Belief Network

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  • Dung Hoang Le

    (University of Information Technology, Vietnam National University, Vietnam)

  • Nguyen Thanh Vu

    (Ho Chi Minh City University of Food Industry, Vietnam)

  • Tuan Dinh Le

    (Long An University of Economics and Industry, Vietnam)

Abstract

This paper proposes a smart system of virus detection that can classify a file as benign or malware with high accuracy detection rate. The approach is based on the aspects of the artificial immune system, in which an artificial immune network is used as a pool to create and develop virus detectors that can detect unknown data. Besides, a deep learning model is also used as the main classifier because of its advantages in binary classification problems. This method can achieve a detection rate of 99.08% on average, with a very low false positive rate.

Suggested Citation

  • Dung Hoang Le & Nguyen Thanh Vu & Tuan Dinh Le, 2021. "A Smart System of Malware Detection Based on Artificial Immune Network and Deep Belief Network," International Journal of Information Security and Privacy (IJISP), IGI Global, vol. 15(1), pages 1-25, January.
    • Handle: RePEc:igg:jisp00:v:15:y:2021:i:1:p:1-25
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