Mobile Botnet Detection

“Mobile Botnet Detection”

Aftab Mulla1, PranayJadhav2, GauravBhoi3, SumitRaj4, Mrs.SinuNambiar5,Ms.Anamika Wasnik6

1,2,3,4,5,6 Dept. of Computer Science Engineering

1,2,3,4,5,6 Dr. D.Y. Patil Institute of Technology, Pune, Maharashtra, India

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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 plat- form. 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.

Keywords: SVM or Support Vector Machine, SQLite Database, botnet, dataset.