research-article

A biometric cryptosystem scheme based on random projection and neural network

Authors:

Ahmed A. Abd El-LatifAuthors Info & Claims

Soft Computing, Volume 25, Issue 11

Pages 7657 - 7670

https://doi.org/10.1007/s00500-021-05732-2

Published: 01 June 2021 Publication History

Abstract

Several biometric cryptosystem techniques have been proposed to protect biometric templates and preserve users’ privacy. Although such techniques can thwart different attacks, it is difficult to achieve well non-linkability between biometric cryptosystems. In this paper, we propose a novel biometric cryptosystem scheme based on random projection (RP) and back propagation neural network (BPNN) to perform the task of biometric template protection. With the help of RP, an original biometric feature vector can be projected onto a fix-length feature vector of random subspace that is derived from a user-specific projection matrix. This process is revocable and produces unlinkable biometric templates. The proposed scheme further utilizes a BPNN model to bind a projected feature vector with a random key. Based on BPNN, a robust mapping between a projected feature vector and a random key is learned to generate an error-correction-based biometric cryptosystem. The security of the proposed scheme is analyzed and the experimental results on multiple biometric datasets show the feasibility and efficiency of the proposed scheme.

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Cited By

Huang F(2024)Industrial technology network security measurement in international trade under discrete hopfield neural networkJournal of Computational Methods in Sciences and Engineering10.3233/JCM-23712824:2(657-674)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.3233/JCM-237128
Kaur PKumar NSingh M(2023)Biometric cryptosystems: a comprehensive surveyMultimedia Tools and Applications10.1007/s11042-022-13817-982:11(16635-16690)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s11042-022-13817-9
Wu TLeng LKhan M(2022)A multi-spectral palmprint fuzzy commitment based on deep hashing code with discriminative bit selectionArtificial Intelligence Review10.1007/s10462-022-10334-x56:7(6169-6186)Online publication date: 21-Nov-2022
https://dl.acm.org/doi/10.1007/s10462-022-10334-x

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Information

Published In

cover image Soft Computing - A Fusion of Foundations, Methodologies and Applications

Soft Computing - A Fusion of Foundations, Methodologies and Applications Volume 25, Issue 11

Jun 2021

447 pages

ISSN:1432-7643

EISSN:1433-7479

Issue’s Table of Contents

© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021. corrected publication 2021.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 June 2021

Accepted: 02 March 2021

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Funding Sources

Heilongjiang Provincial Natural Science Foundation of China (Grant No.LH2020F044),the 2019 “Chunhui Plan” Cooperative Scientific Research Project of Ministry of Education of China
Fundamental Research Funds for Heilongjiang Universities, China (Grant Number: Heilongjiang University Special Fund Project, KJCX202015)

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Cited By

Huang F(2024)Industrial technology network security measurement in international trade under discrete hopfield neural networkJournal of Computational Methods in Sciences and Engineering10.3233/JCM-23712824:2(657-674)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.3233/JCM-237128
Kaur PKumar NSingh M(2023)Biometric cryptosystems: a comprehensive surveyMultimedia Tools and Applications10.1007/s11042-022-13817-982:11(16635-16690)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s11042-022-13817-9
Wu TLeng LKhan M(2022)A multi-spectral palmprint fuzzy commitment based on deep hashing code with discriminative bit selectionArtificial Intelligence Review10.1007/s10462-022-10334-x56:7(6169-6186)Online publication date: 21-Nov-2022
https://dl.acm.org/doi/10.1007/s10462-022-10334-x

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