User Classification for Keystroke Dynamics Authentication

  • Sylvain Hocquet
  • Jean-Yves Ramel
  • Hubert Cardot
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

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.

Keywords

keystroke dynamics clustering parameters adaptation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Sylvain Hocquet
    • 1
  • Jean-Yves Ramel
    • 1
  • Hubert Cardot
    • 1
  1. 1.Université François Rabelais de Tours, Laboratoire d’Informatique (EA 2101), 64 Avenue Jean Portalis, 37200 TOURSFrance

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