Paper Info
Title
FAMOUS: Forensic Analysis of MObile devices Using Scoring of application permissions.
Abstract
With the emergence of Android as a leading operating system in mobile devices, it becomes mandatory to develop specialized, predictive and robust security measures to provide a dependable environment for users. Extant reactive and proactive security techniques would not be enough to tackle the fast-growing security challenges in the Android environment. This paper has proposed a predictive forensic approach to detect suspicious Android applications. An in-depth study of statistical properties of permissions used by the malicious and benign Android applications has been performed. Based on the results of this study, a weighted score based feature set has been created which is used to build a predictive and lightweight malware detector for Android devices. Various experiments conducted on the aforementioned feature set, an improved accuracy level of 99% has been achieved with Random Forest classifier. This trained model has been used to build a forensic tool entitled FAMOUS (F orensic A nalysis of MO bile devices U sing S coring of application permissions) which is able to scan all the installed applications of an attached device and provide a descriptive report.
Year
DOI
Venue
2018
10.1016/j.future.2018.02.001
Future Generation Computer Systems
Keywords
Field
DocType
Apk permissions,Static analysis,Weighted feature,Machine learning,Android malware triage,Forensic triage tool
Android (operating system),Computer science,Real-time computing,Feature set,Mobile device,Extant taxon,Random forest,Malware,Detector,Database
Journal
Volume
ISSN
Citations 
83
0167-739X
4
PageRank 
References 
Authors
0.43
34
3
Name
Order
Citations
PageRank
Ajit Kumar1121.33
K. S. Kuppusamy23414.65
G. Aghila31911.85