Analysis of Keystroke Dynamics For the Generation of Synthetic Datasets

Denis Migdal 1 Christophe Rosenberger 2
1 Equipe Monétique & Biométrie - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
2 Monétique & Biométrie
LVR - Laboratoire de Vision et Robotique
Abstract : Biometrics is an emerging technology more and more present in our daily life. However, building biometric systems requires a large amount of data that may be difficult to collect. Collecting such sensitive data is also very time consuming and constrained, s.a. GDPR legislation. In the case of keystroke dynamics, existing databases have less than 200 users. For these reasons, we aim at generating a keystroke dynamics synthetic dataset. This paper presents the generation of keystroke data from known users as a first step towards the generation of synthetic datasets, and could also be used to impersonate users' identity. Results were also found for user generation, but are not part of this paper.
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Denis Migdal, Christophe Rosenberger. Analysis of Keystroke Dynamics For the Generation of Synthetic Datasets. CyberWorlds, Oct 2018, Singapour, Singapore. ⟨10.1109/CW.2018.00068⟩. ⟨hal-01862152⟩

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