Detecting Mobile Application Spoofing Attacks By Leveraging User Visual Similarity Perception

Mobile application spoofing is an attack where a malicious mobile app mimics the visual appearance of another one. A common example of mobile application spoofing is a phishing attack where the adversary tricks the user into revealing her password to a malicious app that resembles the legitimate one. In this paper, we propose a novel spoofing detection approach, tailored to the protection of mobile app login screens, using screenshot extraction and visual similarity comparison. We use deception rate as a novel similarity metric for measuring how likely the user is to consider a potential spoofing app as one of the protected applications. We conducted a large-scale online study where participants evaluated spoofing samples of popular mobile app login screens, and used the study results to implement a detection system that accurately estimates deception rate. We show that efficient detection is possible with low overhead.