JOURNAL ARTICLE

SEMBA: secure multi‐biometric authentication

Mauro BarniGiulia DroandiRiccardo LazzerettiTommaso Pignata

Year: 2019 Journal:   IET Biometrics Vol: 8 (6)Pages: 411-421   Publisher: Institution of Engineering and Technology

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 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 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.

Keywords:
Biometrics Computer science Computer security Encryption Protocol (science) Leverage (statistics) Cryptography Cryptographic protocol Password Information leakage Authentication (law) Authentication protocol Artificial intelligence

Metrics

33
Cited By
2.96
FWCI (Field Weighted Citation Impact)
57
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Biometric Identification and Security
Physical Sciences →  Computer Science →  Signal Processing
User Authentication and Security Systems
Physical Sciences →  Computer Science →  Information Systems
Face recognition and analysis
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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