Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review

被引:6
|
作者
Alzubaidi, Abdulaziz [1 ]
机构
[1] Umm Al Qura Univ, Coll Comp Al Qunfudhah, Comp Sci Dept, Mecca 24381, Saudi Arabia
关键词
Malware; Smart phones; Trojan horses; Feature extraction; Task analysis; Servers; Performance evaluation; Smartphone; intrusion detection; mobile malware; android devices; machine learning; CLASSIFIER; REGRESSION; SECURITY;
D O I
10.1109/ACCESS.2021.3123187
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, the global pervasiveness of smartphones has prompted the development of millions of free and commercially available applications. These applications allow users to perform various activities, such as communicating, gaming, and completing financial and educational tasks. These commonly used devices often store sensitive private information and, consequently, have been increasingly targeted by harmful malicious software. This paper focuses on the concepts and risks associated with malware, and reviews current approaches and mechanisms used to detect malware with respect to their methodology, associated datasets, and evaluation metrics.
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页码:146318 / 146349
页数:32
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