Using weighted based feature selection technique for android malware detection

Abstract

Recently, the popularity of mobile devices has risen drastically due to the increased functionality of the devices. This matter forces a large number of security challenges that need high consideration. Android malware detection method can be divided into two types, which are static and dynamic analysis. Static techniques are often prone to high false negative rates due to evolution in code basis and code repacking, although fast and efficient. While dynamic and behavior based analysis aims to provide methods for effectively and efficiently extracting unique patterns of each malware family based on its behavior. To address some of those shortcomings, the study uses permission-based Android malware feature as a basis for malware detection using weighted based technique.