Android malware detection from Google Play meta-data: Selection of important features

Android malware has emerged in the last decade as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features to identify patterns often observed in malware applications. We show that modern Machine Learning techniques applied to collected metadata from Google Play can provide a first approach towards the detection of malware applications, and we further identify which features have the highest predictive power among the total.