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

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

Dung Hoang Le, Nguyen Thanh Vu, Tuan Dinh Le
Copyright: © 2021 |Volume: 15 |Issue: 1 |Pages: 25
ISSN: 1930-1650|EISSN: 1930-1669|EISBN13: 9781799859864|DOI: 10.4018/IJISP.2021010101
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MLA

Le, Dung Hoang, et al. "A Smart System of Malware Detection Based on Artificial Immune Network and Deep Belief Network." IJISP vol.15, no.1 2021: pp.1-25. http://doi.org/10.4018/IJISP.2021010101

APA

Le, D. H., Vu, N. T., & Le, T. D. (2021). A Smart System of Malware Detection Based on Artificial Immune Network and Deep Belief Network. International Journal of Information Security and Privacy (IJISP), 15(1), 1-25. http://doi.org/10.4018/IJISP.2021010101

Chicago

Le, Dung Hoang, Nguyen Thanh Vu, and Tuan Dinh Le. "A Smart System of Malware Detection Based on Artificial Immune Network and Deep Belief Network," International Journal of Information Security and Privacy (IJISP) 15, no.1: 1-25. http://doi.org/10.4018/IJISP.2021010101

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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.

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