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

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Author(s): Dung Hoang Le (University of Information Technology, Vietnam National University, Vietnam), Nguyen Thanh Vu (Ho Chi Minh City University of Food Industry, Vietnam)and Tuan Dinh Le (Long An University of Economics and Industry, Vietnam)
Copyright: 2021
Volume: 15
Issue: 1
Pages: 25
Source title: International Journal of Information Security and Privacy (IJISP)
Editor(s)-in-Chief: Yassine Maleh (Sultan Moulay Slimane University, Morocco)and Ahmed A. Abd El-Latif (Menoufia University, Egypt)
DOI: 10.4018/IJISP.2021010101

Keywords: Information Science Reference / Information Security & Privacy / IT Security and Ethics / Security & Forensics

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

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