We have developed a new user authentication method based on eye scanpaths on multiple images. Even for the same images eye scanpaths vary from person to person and are reflexive without any intentional control for absolutely safe authentication. It may be regarded as an interview approach for user authentication, but questions and answers are made on the basis of visual images and eye scanpaths, respectively.

Professor Soo-Young Lee’s team has studied brain internal states, which are responsible for different responses from the same stimuli. One important internal state is preference, which is reflected by differences in eye movements between subjects viewing the same visual images.

The present work repeatedly measured human eye movements at various time intervals that ranged from less than one hour to one year between recording sessions. Subjects observed multiple images with multiple areas of interest, and the eye movements of individuals were compared. The results indicate that within-subject eye movements remain more similar than between-subject eye movements over time. Also, we demonstrated that the user authentication accuracy increased with the increased number of image-to-eye movement trials.

Figure 1. Examples of scanpaths in a 2D coordinate system for two stimulating images and three subjects. The starting point of each scanpath is marked with an asterisk (*) and the end point with a circle (o). Each subject’s scanpaths during observations of an image set are plotted together on the image set. Wn demotes experiments in the n’th week. T1 and T2 denote the first and second experiments with 30 minute intervals.
Figure 1. Examples of scanpaths in a 2D coordinate system for two stimulating images and three subjects. The starting point of each scanpath is marked with an asterisk (*) and the end point with a circle (o). Each subject’s scanpaths during observations of an image set are plotted together on the image set. Wn demotes experiments in the n’th week. T1 and T2 denote the first and second experiments with 30 minute intervals.
Figure 2. Trial-level subject identification rate for each evaluation session. Trial-level subject identification rates within preference selection task sessions were significantly higher than those within free sessions. Average session-level subject identification rates improved to 91.4% for free sessions and 93.2% for task sessions.
Figure 2. Trial-level subject identification rate for each evaluation session. Trial-level subject identification rates within preference selection task sessions were significantly higher than those within free sessions. Average session-level subject identification rates improved to 91.4% for free sessions and 93.2% for task sessions.
Contact Information:
Lee, Soo-Young, Jung, Eunsoo and Lee, DongGeun (School of Electrical Engineering)
Homepage: https://sites.google.com/site/cnslkaist/research/brain-based-user-authentication