Increasing the security of gaze-based cued-recall graphical passwords using saliency masks

  • Authors:
  • Andreas Bulling;Florian Alt;Albrecht Schmidt

  • Affiliations:
  • University of Cambridge & Lancaster University, Cambridge, United Kingdom;University of Stuttgart, Stuttgart, Germany;University of Stuttgart, Stuttgart, Germany

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2012

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Abstract

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.