User classification for keystroke dynamics authentication

Authors:
Sylvain Hocquet;Jean-Yves Ramel;Hubert Cardot
Affiliations:
Université François Rabelais de Tours, Laboratoire d'Informatique,Tours, France;Université François Rabelais de Tours, Laboratoire d'Informatique,Tours, France;Université François Rabelais de Tours, Laboratoire d'Informatique,Tours, France
Venue:
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Year:
2007

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Abstract

In this paper, we propose a method to realize a classification of keystroke dynamics users before performing user authentication. The objective is to set automatically the individual parameters of the classification method for each class of users. Features are extracted from each user learning set, and then a clustering algorithm divides the user set in clusters. A set of parameters is estimated for each cluster. Authentication is then realized in a two steps process. First the users are associated to a cluster and second, the parameters of this cluster are used during the authentication step. This two steps process provides better results than system using global settings.