We investigate the use of gaze behaviour as a means to assess password strength. We contribute to the effort of making users choose passwords that are robust against guessing-attacks. While password policies and meters demonstrated the potential to increase password strength, these approaches provide important cues to attackers as well. Eye tracking enables a novel approach: by analysing people‘s gaze behaviour during password creation, its strength can be determined without revealing its properties. To demonstrate the feasibility of this approach, we present a proof of concept study (N=15) in which we let participants enter weak and strong passwords. Our findings reveal that it is possible to estimate password strength from gaze behaviour using Machine Learning techniques. In this way, we enable research on novel interfaces that motivate people to come-up with stronger passwords.    «

We investigate the use of gaze behaviour as a means to assess password strength. We contribute to the effort of making users choose passwords that are robust against guessing-attacks. While password policies and meters demonstrated the potential to increase password strength, these approaches provide important cues to attackers as well. Eye tracking enables a novel approach: by analysing people‘s gaze behaviour during password creation, its strength can be determined without revealing its proper...    »