Instance-based anomaly method for Android malware detection

Abstract

The usage of mobile phones has increased in our lives because they offer nearly the same functionality as a personal computer. Besides, the number of applications available for Android-based mobile devices has increased. Android application distribution is based on a centralized market where the developers can upload and sell their applications. However, as it happens with any popular service, it is prone to misuse and, in particular, malware writers can use this market to upload their malicious creations. In this paper, we propose a new method that, based upon several features that are extracted from the AndroidManifest file of the legitimate applications, builds an anomaly detection system able to detect malware.