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International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

A Survey on Malware Classification Using Machine Learning and Deep Learning

Author NameAuthor Details

Manish Goyal, Raman Kumar

Manish Goyal[1]

Raman Kumar[2]

[1]Department of Computer Science and Engineering, IK Gujral Punjab Technical University, Kapurthala, Punjab, India

[2]Department of Computer Science and Engineering, IK Gujral Punjab Technical University, Kapurthala, Punjab, India

Cite this Article

DOI: 10.22247/ijcna/2021/210724

Pages : 758-775

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Abstract

In today’s era, there is fast development in the field of Information Technology. It is a matter of great concern for cyber professionals to maintain security and privacy. Studies revealed that the number of new malware is increasing tremendously. It is a never-ending cycle between the world of attack and the defense of malicious software. Antivirus companies are always putting their efforts to develop signatures of malicious software and attackers are always in try to overcome those signatures. For the detection of malware machine learning are highly efficient. The process of detection of malware is split into two categories first is feature extraction and the second is malware classification. The effectiveness of classification algorithms depends on the feature extracted. In this paper, firstly an in-depth study of the features is provided that can be used to differentiate malware. Thereafter describe the various stages of machine learning and deep learning that researchers use in their research work and the pros and cons they face that can assist new researchers while selecting an algorithm for their research work.

Index Terms

Malware Detection

Static Analysis

Dynamic Analysis

Security

Features of Malware

Machine Learning

Deep Learning

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