Analysis of Doddington Zoo Classification for User Dependent Template Update: Application to Keystroke Dynamics Recognition

Abir Mhenni (1, 2) , Estelle Cherrier (1) , Christophe Rosenberger (1) , Najoua Essoukri Ben Amara (2)

1 Equipe SAFE - Laboratoire GREYC - UMR6072
2 LATIS - Laboratory of Advanced Technology and Intelligent Systems

Biometric authentication systems are increasingly considered in different access control applications. Regarding that users have completely different interactions with these authentication systems, several techniques have been developed in the literature to model distinctive users categories. Doddington zoo is a biometric menagerie that defines and labels user groups with animal species to reflect their behavior with the biometric systems. This menagerie was developed for different biometric modalities including keystroke dynamics. The present study proposes a user dependent adaptive strategy based on the Doddinghton zoo, for the recognition of the user's keystroke dynamics. The novelty of the proposed approach lies in applying an adaptive strategy specific to the characteristics of each user of the Doddinghton zoo menagerie aiming to solve the intra-class variation problems. The obtained results demonstrate competitive performances on significant keystroke dynamics datasets WEBGREYC and CMU.

Mots clés: Keystroke dynamics authentication; Password security; Adaptive strategy; Doddington zoo classification; KNN-GA

Domaines: Cryptographie et sécurité [cs.CR]

Abir Mhenni, Estelle Cherrier, Christophe Rosenberger, Najoua Essoukri Ben Amara. Analysis of Doddington Zoo Classification for User Dependent Template Update: Application to Keystroke Dynamics Recognition. Future Generation Computer Systems, 2019. ⟨hal-02050173⟩