Learning a policy for gesture-based active multi-touch authentication

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Abstract

Multi-touch tablets can offer a large, collaborative space where several users can work on a task at the same time. However, the lack of privacy in these situations makes standard password-based authentication easily compromised. This work presents a new gesture-based authentication system based on users' unique signature of touch motion when drawing a combination of one-stroke gestures following two different policies, one fixed for all users and the other selected by a model of control to maximize the expected long-term information gain. The system is able to achieve high user recognition accuracy with relatively few gestures, demonstrating that human touch patterns have a distinctive "signature" that can be used as a powerful biometric measure for user recognition and personalization. © 2013 Springer-Verlag Berlin Heidelberg.

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APA

Peralta, R. T., Rebguns, A., Fasel, I. R., & Barnard, K. (2013). Learning a policy for gesture-based active multi-touch authentication. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8030 LNCS, pp. 59–68). Springer Verlag. https://doi.org/10.1007/978-3-642-39345-7_7

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