Android Malware Family Classification and Analysis: Current Status and Future Directions

被引:30
|
作者
Alswaina, Fahad [1 ]
Elleithy, Khaled [1 ]
机构
[1] Univ Bridgeport, Dept Comp Sci & Engn, Bridgeport, CT 06604 USA
关键词
android malware family; malicious application; android security; android application; machine learning; classification; smartphone; FEATURES; CODE;
D O I
10.3390/electronics9060942
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1 / 20
页数:20
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