Title :
Droid permission miner: Mining prominent permissions for Android malware analysis
Author :
Aswini, A.M. ; Vinod, P.
Author_Institution :
Dept. of Comput. Sci. & Eng., SCMS Sch. of Eng. & Technol., Karukutty, India
Abstract :
In this paper, we propose static analysis of android malware files by mining prominent permissions. The proposed technique is implemented by extracting permissions from 436 .apk files. Feature pruning is carried out to investigate the impact of feature length on accuracy. The prominent features that give way to lesser misclassification are determined using Bi-Normal Separation (BNS) and Mutual Information (MI) feature selection techniques. Results suggest that Droid permission miner can be used for preliminary classification of Android package files.
Keywords :
Android (operating system); data mining; feature selection; invasive software; mobile computing; pattern classification; smart phones; Android package file classification; BNS; Droid permission miner; MI feature selection; android malware analysis; bi-normal separation; mutual information; permission extraction; prominent permission mining; static analysis; Accuracy; Androids; Feature extraction; Humanoid robots; Malware; Smart phones; Training; Androguard; Android malware; Feature extraction; Static analysis;
Conference_Titel :
Applications of Digital Information and Web Technologies (ICADIWT), 2014 Fifth International Conference on the
Conference_Location :
Bangalore
Print_ISBN :
978-1-4799-2258-1
DOI :
10.1109/ICADIWT.2014.6814679
