android malware detection research paper

A Review of Android Malware Detection Approaches Based on Machine Learning

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A comprehensive review on permissions-based Android malware detection

• Regular Contribution
• Published: 04 March 2024
• Volume 23 , pages 1877–1912, ( 2024 )

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• Yash Sharma   ORCID: orcid.org/0000-0002-3255-7159 1 &
• Anshul Arora   ORCID: orcid.org/0000-0001-6316-9055 1  

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The first Android-ready “G1” phone debuted in late October 2008. Since then, the growth of Android malware has been explosive, analogous to the rise in the popularity of Android. The major positive aspect of Android is its open-source nature, which empowers app developers to expand their work. However, authors with malicious intentions pose grave threats to users. In the presence of such threats, Android malware detection is the need of an hour. Consequently, researchers have proposed various techniques involving static, dynamic, and hybrid analysis to address such threats to numerous features in the last decade. However, the feature that most researchers have extensively used to perform malware analysis and detection in Android security is Android permission. Hence, to provide a clarified overview of the latest and past work done in Android malware analysis and detection, we perform a comprehensive literature review using permissions as a central feature or in combination with other components by collecting and analyzing 205 studies from 2009 to 2023. We extracted information such as the choice opted by researchers between analysis or detection, techniques used to select or rank the permissions feature set, features used along with permissions, detection models employed, malware datasets used by researchers, and limitations and challenges in the field of Android malware detection to propose some future research directions. In addition, on the basis of the information extracted, we answer the six research questions designed considering the above factors.

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The Evolution of Permission as Feature for Android Malware Detection

PMDS: Permission-Based Malware Detection System

Research on data mining of permissions mode for android malware detection, data availability.

The authors declare that the data supporting the findings of this study are available within the paper.

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Sharma, Y., Arora, A. A comprehensive review on permissions-based Android malware detection. Int. J. Inf. Secur. 23 , 1877–1912 (2024). https://doi.org/10.1007/s10207-024-00822-2

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• Android security
• Android malware
• Permissions based detection
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• Mobile security
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