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Mobile Application Impersonation Detection Using Dynamic User Interface Extraction
[chapter]
2016
Lecture Notes in Computer Science
In this paper we present a novel approach for detection of mobile app impersonation attacks. Our system uses dynamic code analysis to extract user interfaces from mobile apps and analyzes the extracted screenshots to detect impersonation. As the detection is based on the visual appearance of the application, as seen by the user, our approach is robust towards the attack implementation technique and resilient to simple detection avoidance methods such as code obfuscation. We analyzed over
doi:10.1007/978-3-319-45744-4_11
fatcat:w2m4k4p5xvb53ka3ve5pgliewy