Abstract
User authentication is an important and usually final barrier to detect and prevent illicit access. Nonetheless it can be broken or tricked, leaving the system and its data vulnerable to abuse. In this paper we consider how eye tracking can enable the system to hypothesize if the user is familiar with the system he operates, or if he is an unfamiliar intruder. Based on an eye tracking experiment conducted with 12 users and various stimuli, we investigate which conditions and measures are most suited for such an intrusion detection. We model the user’s gaze behavior as a selector for information flow via the relative conditional gaze entropy. We conclude that this feature provides the most discriminative results with static and repetitive stimuli.
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© 2012 Springer Science+Business Media Dortdrecht
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Biedert, R., Frank, M., Martinovic, I., Song, D. (2012). Stimuli for Gaze Based Intrusion Detection. In: J. (Jong Hyuk) Park, J., Leung, V., Wang, CL., Shon, T. (eds) Future Information Technology, Application, and Service. Lecture Notes in Electrical Engineering, vol 164. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4516-2_80
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DOI: https://doi.org/10.1007/978-94-007-4516-2_80
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