Title
Lumus: Dynamically Uncovering Evasive Android Applications
Abstract
Dynamic analysis of Android malware suffers from techniques that identify the analysis environment and prevent the malicious behavior from being observed. While there are many analysis solutions that can thwart evasive malware on Windows, the application of similar techniques for Android has not been studied in-depth. In this paper, we present Lumus, a novel technique to uncover evasive malware on Android. Lumus compares the execution traces of malware on bare metal and emulated environments. We used Lumus to analyze 1,470 Android malware samples and were able to uncover 192 evasive samples. Comparing our approach with other solutions yields better results in terms of accuracy and false positives. We discuss which information are typically used by evasive malware for detecting emulated environments, and conclude on how analysis sandboxes can be strengthened in the future.
Year
DOI
Venue
2018
10.1007/978-3-319-99136-8_3
INFORMATION SECURITY (ISC 2018)
Field
DocType
Volume
Android (operating system),Computer security,Computer science,Android malware,Malware,False positive paradox
Conference
11060
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
23
6