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Keystroke Dynamics Anonymization System

Denis Migdal 1 Christophe Rosenberger 1
1 Equipe Monétique & Biométrie - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : Keystroke Dynamics enables the authentication or identification of users by analyzing their way of typing, e.g. when browsing the Internet. Most studies in the state of the art focus on increasing Keystroke Dynamics Sys- tems performances. In this paper, we address the problematic of avoiding the biometric capture of keystroke dynamics in order to protect users’ privacy. Authentication/identification, profiling can be considered as at- tacks we limit in this contribution. Experimental results obtained on significant datasets show the benefits of the proposed approaches.
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Contributor : Denis Migdal <>
Submitted on : Sunday, August 11, 2019 - 2:19:10 PM
Last modification on : Monday, August 12, 2019 - 11:41:20 AM
Long-term archiving on: : Thursday, January 9, 2020 - 4:05:58 PM


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  • HAL Id : hal-02126985, version 1


Denis Migdal, Christophe Rosenberger. Keystroke Dynamics Anonymization System. SeCrypt International Conference on Security and Cryptography, Jul 2019, Prague, Czech Republic. ⟨hal-02126985⟩



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