Android Malware Family Classification and Analysis: Current Status and Future Directions
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Authors
Alswaina, Fahad
Elleithy, Khaled M.
Issue Date
2020-06-05
Type
Article
Language
en_US
Keywords
Android malware family , Malicious application , Android security , Android application , Machine learning , Classification , Smartphone
Alternative Title
Abstract
Android receives major attention from security practitioners and researchers due to the influx number of malicious applications. For the past twelve years, Android malicious applications have been grouped into families. In the research community, detecting new malware families is a challenge. As we investigate, most of the literature reviews focus on surveying malware detection. Characterizing the malware families can improve the detection process and understand the malware patterns. For this reason, we conduct a comprehensive survey on the state-of-the-art Android malware familial detection, identification, and categorization techniques. We categorize the literature based on three dimensions: type of analysis, features, and methodologies and techniques. Furthermore, we report the datasets that are commonly used. Finally, we highlight the limitations that we identify in the literature, challenges, and future research directions regarding the Android malware family.
Description
Citation
Alswaina, F.; Elleithy, K. Android Malware Family Classification and Analysis: Current Status and Future Directions. Electronics 2020, 9, 942.
Publisher
MDPI