English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Increasing the Security of Gaze-Based Cued-Recall Graphical Passwords Using Saliency Masks

MPS-Authors
There are no MPG-Authors in the publication available
External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Bulling, A., Alt, F., & Schmidt, A. (2012). Increasing the Security of Gaze-Based Cued-Recall Graphical Passwords Using Saliency Masks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3011-3020). New York, NY: ACM.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0018-6A7C-C
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 pass- words 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\textquoterights 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.