No 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 of processing the biometric signals under encryption, in order to avoid any leakage of information towards non-authorised parties. In this study, the authors propose to leverage on the superior performance of multimodal biometric recognition to improve the efficiency of a biometricbased 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 the trade-off between recognition accuracy and efficiency. From a cryptographic point of view, the protocol relies on Damgård et al. SPDZ. Experimental results show that the multimodal protocol is faster than corresponding unimodal protocols achieving the same accuracy.

Being unique and immutable for each person, biometric signals are widely used in access control systems. While biometric recognition appeases concerns about password's theft or loss, at the same time it raises concerns about individual privacy. Central servers store several enrolled biometrics, hence security against theft must be provided during biometric transmission and against those who have access to the database. If a server's database is compromised, other systems using the same biometric templates could also be compromised as well. One solution is to encrypt the stored templates. Nonetheless, when using traditional cryptosystem, data must be decrypted before executing the protocol, leaving the database vulnerable. To overcame this problem and protect both the server and the client, biometrics should be processed while encrypted. This is possible by using secure two-party computation protocols, mainly based on Garbled Circuits (GC) and additive Homomorphic Encryption (HE). Both GC and HE based solutions are efficient yet interactive, meaning that the client takes part in the computation. Instead in this paper we propose a non-interactive protocol for privacy preserving biometric authentication based on a Somewhat Homomorphic Encryption (SHE) scheme, modified to handle integer values, and also suggest a blinding method to protect the system from spoofing attacks. Although our solution is not as efficient as the ones based on GC or HE, the protocol needs no interaction, moving the computation entirely on the server side and leaving only inputs encryption and outputs decryption to the client.

No 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 biometricbased 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 [1], [2]. Experimental results show that the multimodal protocol is faster than corresponding unimodal protocols achieving the same accuracy.