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Android Malware Detection Techniques in Traditional and Cloud Computing Platforms: A State-of-the-Art Survey

Aayush Vishnoi, Preeti Mishra, Charu Negi and Sateesh Kumar Peddoju
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Aayush Vishnoi: Graphic Era University (Deemed), Dehradun, India
Preeti Mishra: Dept. of CSE, Graphic Era University (Deemed), India & Dept. of CS, Doon University Dehradun, India
Charu Negi: Graphic Era Hill University, Dehradun, India
Sateesh Kumar Peddoju: Indian Institute of Technology, Roorkee, India

International Journal of Cloud Applications and Computing (IJCAC), 2021, vol. 11, issue 4, 113-135

Abstract: In the mobile world, Android is the most popular choice of manufacturers and users alike. Meanwhile, a number of malicious applications abbreviated as malapps or malware have increased explosively. Malware writers make use of existing apps to send malware to users' devices. To check presence of malware, the authors perform malware analysis of apps. In this paper, they provide a comprehensive review on state-of-the-art android malware detection approaches using traditional and cloud computing platforms. The paper also presents attack taxonomy to better understand security threat against Android. Furthermore, it describes various possible attacking features (static and dynamic) and their analysis mechanism. Various security tools have also been discussed. It presents two case studies: one for malware feature extraction and the other for demonstrating the use of machine learning for malware analysis in order to provide a practical insight of malware analysis. The results of malware analysis seem to be promising.

Date: 2021
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International Journal of Cloud Applications and Computing (IJCAC) is currently edited by B. B. Gupta

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