Increasing the Security of Gaze-Based Cued-Recall Graphical Passwords Using Saliency Masks
Date: May 2012
Publication: Proceedings of the 2012 SIGCHI Conference on Human Factors in Computing Systems, CHI '12
Page(s): 3011 - 3020
Source 1: http://perceptual.mpi-inf.mpg.de/files/2013/03/bulling12_chi.pdf
Source 2: http://www.hcilab.org/wp-content/uploads/bulling2012increasing.pdf
Source 3: http://dx.doi.org/10.1145/2207676.2208712 - Subscription or payment required
Abstract or Summary:
With computers being used ever more ubiquitously in situations where privacy is important, secure user authentication is a central requirement. Gaze-based graphical passwords are a particularly promising means for shoulder-surfing-resistant authentication, but selecting secure passwords remains challenging. In this paper, we present a novel gaze-based authentication scheme that makes use of cued-recall graphical passwords on a single image. In order to increase password security, our approach uses a computational model of visual attention to mask those areas of the image that are most likely to attract visual attention. We create a realistic threat model for attacks that may occur in public settings, such as filming the user's interaction while drawing money from an ATM. Based on a 12-participant user study, we show that our approach is significantly more secure than a standard image-based authentication and gaze-based 4-digit PIN entry.
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