An efficient biometric-based continuous authentication scheme with HMM prehensile movements modeling

Feriel Cherifi (1) , Mawloud Omar (2, 3) , Kamal Amroun (1)

1 UB - Université Abderrahmane Mira [Université de Béjaïa] = University Abderrahmane Mira [University of Béjaïa]
2 LIGM - Laboratoire d'Informatique Gaspard-Monge
3 ESIEE Paris

Biometric is an emerging technique for user authentication thanks to its efficiency compared to the traditional methods, such as passwords and access-cards. However, most existing biometric authentication systems require the cooperation of users and provide only a login time authentication. To address these drawbacks, we propose in this paper a new, efficient continuous authentication scheme based on the newly biometric trait that still under development: prehensile movements. In this work, we model the movements through Hidden Markov Model-Universal Background Model (HMM-UBM) with continuous observations based on Gaussian Mixture Model (GMM). Unlike the literature, the gravity signal is included. The results of the experiments conducted on a public database HMOG and on a proprietary database, collected under uncontrolled conditions, have shown that prehensile movements are very promising. This new biometric feature will allow users to be authenticated continuously, passively and in real time.

Mots clés: Biometric; authentication; prehensile movement; HMM-UBM; GMM

Domaines: Intelligence artificielle [cs.AI]; Biomécanique [physics.med-ph]

Feriel Cherifi, Mawloud Omar, Kamal Amroun. An efficient biometric-based continuous authentication scheme with HMM prehensile movements modeling. Journal of information security and applications, 2021, 57, pp.102739. ⟨10.1016/j.jisa.2020.102739⟩. ⟨hal-03091925⟩