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Presentation-level privacy protection techniques for automated face recognition - a survey

Presentation-level privacy protection techniques for automated face recognition - a survey
Presentation-level privacy protection techniques for automated face recognition - a survey
The use of Biometric Facial Recognition (FR) Systems have become increasingly widespread, especially since the advent of deep neural network-based architectures (DNNs). Although FR systems provide substantial benefits in terms of security and safety, the use of these systems also raises significant privacy concerns. This paper discusses recent advances in facial identity hiding techniques, focusing on privacy protection approaches that hide or protect facial biometric data before camera devices capture the data. Moreover, we also discuss the state-of-the-art methods used to evaluate such privacy protection techniques. The primary motivation of this survey is to assess the relative performance of facial privacy protection methods and identify open challenges and future work that needs to be considered in this research area.
General Computer Science, Theoretical Computer Science
0360-0300
Hasan, Md. Rezwan
81389485-48b9-443c-b126-6382a7abddd6
Guest, Richard M.
93533dbd-b101-491b-83cc-39ccfdc18165
Deravi, Farzin
15f7c2ec-bd1e-4819-9ca9-7e179385dfa7
Hasan, Md. Rezwan
81389485-48b9-443c-b126-6382a7abddd6
Guest, Richard M.
93533dbd-b101-491b-83cc-39ccfdc18165
Deravi, Farzin
15f7c2ec-bd1e-4819-9ca9-7e179385dfa7

Hasan, Md. Rezwan, Guest, Richard M. and Deravi, Farzin (2023) Presentation-level privacy protection techniques for automated face recognition - a survey. ACM Computing Surveys, 56 (13s), [286]. (doi:10.1145/3583135).

Record type: Article

Abstract

The use of Biometric Facial Recognition (FR) Systems have become increasingly widespread, especially since the advent of deep neural network-based architectures (DNNs). Although FR systems provide substantial benefits in terms of security and safety, the use of these systems also raises significant privacy concerns. This paper discusses recent advances in facial identity hiding techniques, focusing on privacy protection approaches that hide or protect facial biometric data before camera devices capture the data. Moreover, we also discuss the state-of-the-art methods used to evaluate such privacy protection techniques. The primary motivation of this survey is to assess the relative performance of facial privacy protection methods and identify open challenges and future work that needs to be considered in this research area.

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More information

Accepted/In Press date: 30 January 2023
e-pub ahead of print date: 9 February 2023
Published date: 13 July 2023
Keywords: General Computer Science, Theoretical Computer Science

Identifiers

Local EPrints ID: 489468
URI: http://eprints.soton.ac.uk/id/eprint/489468
ISSN: 0360-0300
PURE UUID: 9bf92d43-ff61-4dc3-b45f-fb81baba1bad
ORCID for Richard M. Guest: ORCID iD orcid.org/0000-0001-7535-7336

Catalogue record

Date deposited: 25 Apr 2024 16:30
Last modified: 28 Apr 2024 02:05

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Contributors

Author: Md. Rezwan Hasan
Author: Richard M. Guest ORCID iD
Author: Farzin Deravi

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