Title: AMBAS: an autonomous multimodal biometric authentication system

Authors: Abdeljebar Mansour; Mohamed Sadik; Essaid Sabir; Mostafa Jebbar

Addresses: NEST Research Group, LRI Laboratory, ENSEM, Hassan II University of Casablanca, Casablanca, Morocco ' NEST Research Group, LRI Laboratory, ENSEM, Hassan II University of Casablanca, Casablanca, Morocco ' NEST Research Group, LRI Laboratory, ENSEM, Hassan II University of Casablanca, Casablanca, Morocco ' LIAD Laboratory, FSAC, Hassan II University of Casablanca, Casablanca, Morocco

Abstract: The traditional authentication techniques based on single factors such as passwords and tokens suffer from problems related to their robustness. Moreover, multi-factor authentication based on multimodal biometrics (MFA-MB) technique is used to overcome the drawbacks related to these techniques and also the problems related to the biometrics using single traits. Based on MFA-MB, this paper aims to model and develop an autonomous multimodal biometric authentication system called 'AMBAS' using discrete-time Markov chains in order to decrease the complexity of the multimodal biometric system used in the MFA-MB scheme. In fact, giving the self-control to the AMBAS will improve therefore one user experience and achieve as well good performances in terms of authentication time. This system aims to identify users according to four different methodologies. While giving a case study with three-modal biometrics, we exhibit the performed algorithms. A simulation is done in order to test the system performances and usefulness.

Keywords: multi-factor authentication; multimodal biometric authentication; MBA; multimodal biometrics; discrete-time Markov chains; DTMCs; autonomous systems; user experience; computer security.

DOI: 10.1504/IJAACS.2019.100753

International Journal of Autonomous and Adaptive Communications Systems, 2019 Vol.12 No.3, pp.187 - 217

Received: 16 Mar 2018
Accepted: 11 Jul 2018
Published online: 17 Jul 2019 *

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