SEMBA:SEcure multi-biometric authentication
This work addresses security threats in biometric authentication for users needing protection against data theft and unauthorized access, representing an incremental improvement in efficiency.
The paper tackled the problem of secure biometric authentication by proposing a multimodal protocol that uses encrypted facial and iris data to improve efficiency without compromising accuracy, achieving faster performance than unimodal approaches.
Biometrics security is a dynamic research area spurred by the need to protect personal traits from threats like theft, non-authorised distribution, reuse and so on. A widely investigated solution to such threats consists in processing the biometric signals under encryption, to avoid any leakage of information towards non-authorised parties. In this paper, we propose to leverage on the superior performance of multimodal biometric recognition to improve the efficiency of a biometric-based authentication protocol operating on encrypted data under the malicious security model. In the proposed protocol, authentication relies on both facial and iris biometrics, whose representation accuracy is specifically tailored to trade-off between recognition accuracy and efficiency. From a cryptographic point of view, the protocol relies on SPDZ a new multy-party computation tool designed by Damgaard et al. Experimental results show that the multimodal protocol is faster than corresponding unimodal protocols achieving the same accuracy.