Mobile Botnet Detection

Abstract

Android, being the most widespread mobile operating systems is increasingly becoming a target for malware. Malicious apps designed to turn mobile devices into bots that may form part of a larger botnet have become quite common, thus posing a serious threat. This calls for more effective methods to detect botnets on the Android platform. Hence, in this paper, we present a deep learning approach for Android botnet detection based on Support vector machine (SVM). Our proposed botnet detection system is implemented as a svm based model that is trained on 342 static app features to distinguish between botnet apps and normal apps.