DocumentCode
3658054
Title
Potential Component Leaks in Android Apps: An Investigation into a New Feature Set for Malware Detection
Author
Li Li;Kevin Allix;Daoyuan Li;Alexandre Bartel;Tegawendé F. Bissyandé;Jacques Klein
Author_Institution
SnT, Univ. of Luxembourg, Luxembourg, Luxembourg
fYear
2015
Firstpage
195
Lastpage
200
Abstract
We discuss the capability of a new feature set for malware detection based on potential component leaks (PCLs). PCLs are defined as sensitive data-flows that involve Android inter-component communications. We show that PCLs are common in Android apps and that malicious applications indeed manipulate significantly more PCLs than benign apps. Then, we evaluate a machine learning-based approach relying on PCLs. Experimental validations show high performance for identifying malware, demonstrating that PCLs can be used for discriminating malicious apps from benign apps.
Keywords
"Malware","Androids","Humanoid robots","Feature extraction","Libraries","Machine learning algorithms","Training"
Publisher
ieee
Conference_Titel
Software Quality, Reliability and Security (QRS), 2015 IEEE International Conference on
Type
conf
DOI
10.1109/QRS.2015.36
Filename
7272932
Link To Document