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Privacy–enhancing face biometrics : a comprehensive survey
ID Meden, Blaž (Author), ID Rot, Peter (Author), ID Terhörst, Philipp (Author), ID Damer, Naser (Author), ID Kuijper, Arjan (Author), ID Scheirer, Walter J. (Author), ID Ross, Arun Abraham (Author), ID Peer, Peter (Author), ID Štruc, Vitomir (Author)

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Abstract
Biometric recognition technology has made significant advances over the last decade and is now used across a number of services and applications. However, this widespread deployment has also resulted in privacy concerns and evolving societal expectations about the appropriate use of the technology. For example, the ability to automatically extract age, gender, race, and health cues from biometric data has heightened concerns about privacy leakage. Face recognition technology, in particular, has been in the spotlight, and is now seen by many as posing a considerable risk to personal privacy. In response to these and similar concerns, researchers have intensified efforts towards developing techniques and computational models capable of ensuring privacy to individuals, while still facilitating the utility of face recognition technology in several application scenarios. These efforts have resulted in a multitude of privacy–enhancing techniques that aim at addressing privacy risks originating from biometric systems and providing technological solutions for legislative requirements set forth in privacy laws and regulations, such as GDPR. The goal of this overview paper is to provide a comprehensive introduction into privacy–related research in the area of biometrics and review existing work on Biometric Privacy–Enhancing Techniques (B–PETs) applied to face biometrics. To make this work useful for as wide of an audience as possible, several key topics are covered as well, including evaluation strategies used with B–PETs, existing datasets, relevant standards, and regulations and critical open issues that will have to be addressed in the future.

Language:English
Keywords:image based biometrics, face recognition, privacy, privacy–enhancing techniques, biometrics, data privacy, online social networking, image recognition, security, regulation
Work type:Article
Typology:1.02 - Review Article
Organization:FRI - Faculty of Computer and Information Science
FE - Faculty of Electrical Engineering
Publication status:Published
Publication version:Version of Record
Year:2021
Number of pages:Str. 4147-4183
Numbering:Vol. 16
PID:20.500.12556/RUL-144727 This link opens in a new window
UDC:004.93:57.087.1
ISSN on article:1556-6013
DOI:10.1109/TIFS.2021.3096024 This link opens in a new window
COBISS.SI-ID:74973443 This link opens in a new window
Publication date in RUL:09.03.2023
Views:665
Downloads:116
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Record is a part of a journal

Title:IEEE transactions on information forensics and security
Publisher:Institute of Electrical and Electronics Engineers
ISSN:1556-6013
COBISS.SI-ID:5202004 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:slikovna biometrija, prepoznavanje obrazov, zasebnost, tehnike izboljšave zasebnosti

Projects

Funder:ARRS - Slovenian Research Agency
Project number:J2-1734
Name:Deidentifikacija obrazov z globokimi generativnimi modeli (FaceGEN)

Funder:ARRS - Slovenian Research Agency
Project number:P2-0250
Name:Metrologija in biometrični sistemi

Funder:ARRS - Slovenian Research Agency
Project number:P2-0214
Name:Računalniški vid

Funder:Other - Other funder or multiple funders
Funding programme:Germany, Federal Ministry of Education and Research

Funder:Other - Other funder or multiple funders
Funding programme:Hessen, Ministry for Higher Education, Research and the Arts, National Research Center for Applied Cybersecurity ATHENE

Funder:NSF - National Science Foundation
Project number:1618518

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