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Title: Detecting Sensor-Based Repackaged Malware
Android is the most targeted mobile OS. Studies have found that repackaging is one of the most common techniques that adversaries use to distribute malware, and detecting such malware can be difficult because they share large parts of the code with benign apps. Other studies have highlighted the privacy implications of zero-permission sensors. In this work, we investigate if repackaged malicious apps utilize more sensors than the benign counterpart for malicious purposes. We analyzed 15,297 app pairs for sensor usage. We provide evidence that zero-permission sensors are indeed used by malicious apps to perform various activities. We use this information to train a robust classifier to detect repackaged malware in the wild.  more » « less
Award ID(s):
1563555 1815494
NSF-PAR ID:
10283058
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
IEEE International Conference on Big Data (Big Data)
Page Range / eLocation ID:
5759 to 5761
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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