A New Framework for Match on Card and Match on Host Quality Based Multimodal Biometric Authentication


Smart cards are widely used to deploy secure and cost effective identity management systems. Integration of biometrics into the smart card leads to a strong two-factor authentication system through the match on card (MOC) process. Since MOC uses fixed authentication strategies during the life cycle of smart card, this leads to a low performance and high failure to acquire error in uncontrolled noisy environments. To solve this problem, this paper proposes a sequential quality based framework for biometric authentication. In the proposed framework a set of classifiers have been used to manage the workflow of the framework based on the quality of samples. Accordingly, subjects can be dynamically authenticated using MOC and MOH. A multimodal chimera database is used to evaluate this framework. Our findings indicate that the proposed approach provides higher accuracy than the unimodal MOC and MOH by 11.29% and 5.12%, respectively. Furthermore, the proposed framework can authenticate 83.85% of users without auxiliary trait at the expense of only 1.21% lower accuracy compared to parallel fusion, which require acquisition of all traits for entire users. Analysis of the results demonstrates that the proposed approach provides a compromise between accuracy, user convenience, security and system complexity.

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Correspondence to Mohammad-Shahram Moin.

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Sabri, M., Moin, M. & Razzazi, F. A New Framework for Match on Card and Match on Host Quality Based Multimodal Biometric Authentication. J Sign Process Syst 91, 163–177 (2019). https://doi.org/10.1007/s11265-018-1385-4

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  • Multimodal biometrics
  • Authentication
  • Match on card
  • Score level fusion