BRIDEMAID: An Hybrid Tool for Accurate Detection of Android Malware

Abstract

This paper presents BRIDEMAID, a framework which exploits an approach static and dynamic for accurate detection of Android malware. The static analysis is based on n-grams matching, whilst the dynamic analysis is based on multi-level monitoring of device, app and user behavior. The framework has been tested against 2794 malicious apps reporting a detection accuracy of 99,7% and a negligible false positive rate, tested on a set of 10k genuine apps.