Android Malware Detection Techniques in Traditional and Cloud Computing Platforms

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.