Sensitivity analysis of static features for Android malware detection
Samaneh Hosseini Moghaddam, Maghsoud Abbaspour · 2014
The recent explosion of the number of mobile malware in the wild, significantly increases the importance of developing techniques to detect them. There are many published research in this area which employed traditional desktop malware detection approaches like dynamic and static analysis techniques to detect mobile malwares, but none of them applied a thorough study on the sensitivity analysis of the features used. In this paper we divide static features of classification-based Android malware detection techniques proposed in different papers into some related categories and study the influence of using each category of features on the efficiency of classification-based Android malware detections technique using all the static features.