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

被引：1

作者：

Dung Hoang Le ^{[1
]}

Nguyen Thanh Vu ^{[2
]}

Tuan Dinh Le ^{[3
]}

机构：

[1] Vietnam Natl Univ, Univ Informat Technol, Hanoi, Vietnam

[2] Ho Chi Minh City Univ Food Ind, Ho Chi Minh City, Vietnam

[3] Long An Univ Econ & Ind, Tan An City, Long An, Vietnam

来源：

INTERNATIONAL JOURNAL OF INFORMATION SECURITY AND PRIVACY | 2021年 / 15卷 / 01期

关键词：

Artificial Immune Network; Artificial Immune System; Clonal Selection Algorithm; Deep Belief Network; Negative Selection Algorithm; Portable Executable;

D O I：

10.4018/IJISP.2021010101

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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.

引用

页码：1 / 25

页数：25

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