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A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biomet...

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Detalles Bibliográficos
Autores principales: Yang, Wencheng, Wang, Song, Cui, Hui, Tang, Zhaohui, Li, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098691/
https://www.ncbi.nlm.nih.gov/pubmed/37050626
http://dx.doi.org/10.3390/s23073566
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author Yang, Wencheng
Wang, Song
Cui, Hui
Tang, Zhaohui
Li, Yan
author_facet Yang, Wencheng
Wang, Song
Cui, Hui
Tang, Zhaohui
Li, Yan
author_sort Yang, Wencheng
collection PubMed
description The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics. This survey provides a comprehensive review of state-of-the-art HE research in the context of biometrics. Detailed analyses and discussions are conducted on various HE approaches to biometric security according to the categories of different biometric traits. Moreover, this review presents the perspective of integrating HE with other emerging technologies (e.g., machine/deep learning and blockchain) for biometric security. Finally, based on the latest development of HE in biometrics, challenges and future research directions are put forward.
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spelling pubmed-100986912023-04-14 A Review of Homomorphic Encryption for Privacy-Preserving Biometrics Yang, Wencheng Wang, Song Cui, Hui Tang, Zhaohui Li, Yan Sensors (Basel) Review The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics. This survey provides a comprehensive review of state-of-the-art HE research in the context of biometrics. Detailed analyses and discussions are conducted on various HE approaches to biometric security according to the categories of different biometric traits. Moreover, this review presents the perspective of integrating HE with other emerging technologies (e.g., machine/deep learning and blockchain) for biometric security. Finally, based on the latest development of HE in biometrics, challenges and future research directions are put forward. MDPI 2023-03-29 /pmc/articles/PMC10098691/ /pubmed/37050626 http://dx.doi.org/10.3390/s23073566 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Yang, Wencheng
Wang, Song
Cui, Hui
Tang, Zhaohui
Li, Yan
A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
title A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
title_full A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
title_fullStr A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
title_full_unstemmed A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
title_short A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
title_sort review of homomorphic encryption for privacy-preserving biometrics
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098691/
https://www.ncbi.nlm.nih.gov/pubmed/37050626
http://dx.doi.org/10.3390/s23073566
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