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A Systematic Review of Android Malware Detection Techniques
Faris Auid Alharbi, Abdurhman Mansour Alghamdi, Ahmed S Alghamdi
Pages - 1 - 18     |    Revised - 31-01-2021     |    Published - 28-02-2021
Volume - 15   Issue - 1    |    Publication Date - February 2021  Table of Contents
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KEYWORDS
Malware Detection, Android, Static, Dynamic and Hybrid Detection.
ABSTRACT
Malware detection is a significant key to Android application security. Malwares threat to Android users is increasing day by day. End users need security because they use mobile device to communicate information. Therefore, developing malware detection and control technology should be a priority. This research has extensively explored various state of the art techniques and mechanisms to detect malwares in Android applications by systematic literature review. It categorized the current researches into static, dynamic and hybrid approaches. This research work identifies the limitation and strength current research work. According to the restrictions of current malware detection technologies, it can conclude that detection technologies that use statistical analysis consume more time, energy and resources as compare to machine learning techniques. The results obtained from this research work reinforce the assertion that detection approaches designed for Android malware do not produce 100% efficient detection accuracy.
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Mr. Faris Auid Alharbi
Faculty of Computer Science and Engineering/Cybersecurity, University of Jeddah, Jeddah, 23468, P.O.Box: 4053 - Saudi Arabia
faris-7000@hotmail.com
Mr. Abdurhman Mansour Alghamdi
Faculty of Computer Science and Engineering/Cybersecurity, University of Jeddah, Jeddah, 21959, P.O.Box: 34 - Saudi Arabia
Mr. Ahmed S Alghamdi
College of Computer science and Engineering/Cybersecurity, University of Jeddah, Jeddah, 23465 - Saudi Arabia