SEMBA:SEcure multi-biometric authentication

TL;DR

This paper introduces a multimodal biometric authentication protocol combining face and iris recognition, operating securely on encrypted data with improved efficiency over unimodal methods, leveraging multi-party computation.

Contribution

It presents a novel multimodal biometric protocol using SPDZ for secure encrypted recognition, enhancing speed while maintaining accuracy.

Findings

Multimodal protocol outperforms unimodal in speed for same accuracy

Uses SPDZ multi-party computation for security

Balances recognition accuracy and efficiency

Abstract

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.