Comparative study of k-means and mini batch k-means clustering algorithms in android malware detection using network traffic analysis

This paper evaluates performance of two clustering algorithms, namely k-means and mini batch k-means, in the Android malware detection. Network traffic generated by the Android applications, normal and malicious, is analyzed for detection purpose. We have used MalGenome data sample for this work to build the dataset. We chose 800 samples out of 1260 Android malware samples. In addition, we collected numerous normal applications from the official Android market. The results show that mini batch k-means algorithm performs better than k-means algorithm in the Android malware detection.