AMBAS: an autonomous multimodal biometric authentication system
by Abdeljebar Mansour; Mohamed Sadik; Essaid Sabir; Mostafa Jebbar
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 12, No. 3, 2019

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.

Online publication date: Wed, 17-Jul-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Autonomous and Adaptive Communications Systems (IJAACS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com