Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

Author:

Gorment Nor Zakiah1ORCID,Selamat Ali1ORCID,Cheng Lim Kok2,Krejcar Ondrej1ORCID

Affiliation:

1. Malaysia–Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

2. College of Computing and Informatics, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang, Selangor, Malaysia

Funder

Fundamental Research Grant Scheme (FRGS) through the Ministry of Education

Faculty of Informatics and Management, University of Hradec Kralove, through the Specific Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference127 articles.

1. Malware and malware detection techniques: A survey;Landage;Int. J. Eng. Res. Technol.,2013

2. Asystematic reviewon hybrid analysis using machine learning for Android malware detection;Galib

3. Analysis and Classification of Android Malware using Machine Learning Algorithms

4. Comparison of Machine Learning Methods for Android Malicious Software Classification based on System Call

5. Investigation of Malware Detection Techniques on Smart Phones

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