An Android Behavior-Based Malware Detection Method using Machine Learning
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In this paper, we propose An Android Behavior-Based Malware Detection Method using Machine Learning. We improve an Android application sandbox, Droidbox, by inserting a view-identification automatic trigger program which can click mobile applications in the meaningful order. Taking advantage of Droidbox result, we collect the behavior such as network activities, file read/write and permission as the feature data and use different machine learning algorithms to classify malware and evaluate the performance. We use a large number of malware and normal application samples to prove that our method has high accuracy.
[1] Thomas Schreck,et al. Mobile-Sandbox: combining static and dynamic analysis with machine-learning techniques , 2015, International Journal of Information Security.
[2] Thomas Schreck,et al. Mobile-sandbox: having a deeper look into android applications , 2013, SAC '13.