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Shoulder-surfing resistance with eye-gaze entry in cued-recall graphical passwords
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Increasing the security of gaze-based cued-recall graphical passwords using saliency masks
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Authentication systems for public terminals and thus public spaces have to be fast, easy and secure. Security is of utmost importance since the public setting allows manifold attacks from simple shoulder surfing to advanced manipulations of the terminals. In this work, we present EyePassShapes, an eye tracking authentication method that has been designed to meet these requirements. Instead of using standard eye tracking input methods that require precise and expensive eye trackers, EyePassShapes uses eye gestures. This input method works well with data about the relative eye movement, which is much easier to detect than the precise position of the user's gaze and works with cheaper hardware. Different evaluations on technical aspects, usability, security and memorability show that EyePassShapes can significantly increase security while being easy to use and fast at the same time.