Document Details

Document Type : Article In Journal 
Document Title :
Intelligent Approach for Android Malware Detection
Intelligent Approach for Android Malware Detection
 
Subject : Computer Science 
Document Language : English 
Abstract : As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field. 
ISSN : 1976-7277 
Journal Name : TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 
Volume : 9 
Issue Number : 8 
Publishing Year : 1436 AH
2015 AD 
Article Type : Article 
Added Date : Monday, March 7, 2016 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
Altyeb AltaherAltaher, Altyeb InvestigatorDoctoratealtypaltaher@gmail.com
Shubair M AbdallaAbdalla, Shubair MResearcher shubair@squ.edu.om

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