OTB-morph: One-Time Biometrics via Morphing applied to Face Templates
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Abstract (arXiv)
Cancelable biometrics refers to a group of techniques in which the biometric inputs are transformed intentionally using a key before processing or storage. This transformation is repeatable enabling subsequent biometric comparisons. This paper introduces a new scheme for cancelable biometrics aimed at protecting the templates against potential attacks, applicable to any biometric-based recognition system. Our proposed scheme is based on time-varying keys obtained from morphing random biometric information. An experimental implementation of the proposed scheme is given for face biometrics. The results confirm that the proposed approach is able to withstand against leakage attacks while improving the recognition performance.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 9 of its 52 references that are in the map. First posted on arXiv 25 Nov 2021.
Builds on
9 of 52 references.
References · 9
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2019Deep Leakage from Gradientscited by 1,004
- 2017VGGFace2: A dataset for recognising faces across pose and agecited by 911
- 2014Learning Face Representation from Scratchcited by 451
- 2020Face Morphing Attack Generation & Detection: A Comprehensive Surveycited by 63
- 2019GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detectioncited by 42
- 2020DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representationscited by 26
- 2019Biometric Template Storage with Blockchain: A First Look into Cost and Performance Tradeoffscited by 6
- 2020Are Adaptive Face Recognition Systems still Necessary? Experiments on the APE Datasetcited by 1
Built on by
Citing papers per year: 2023: 4.
4 papers.
- 2023Toward Face Biometric De-identification using Adversarial Examplescited by 8
- 2023OTB-morph: One-Time Biometrics via Morphingcited by 5
- 2023SaFL: Sybil-aware Federated Learning with Application to Face Recognitioncited by 2
- 2023Blockchain and Biometrics: Survey, GDPR Analysis, and Future Directionscited by 1
- 2023SaFL: Sybil-aware Federated Learning with Application to Face Recognition7 Nov 2023
- 2023Blockchain and Biometrics: Survey, GDPR Analysis, and Future Directions21 Feb 2023
- 2023OTB-morph: One-Time Biometrics via Morphing17 Feb 2023
- 2023Toward Face Biometric De-identification using Adversarial Examples7 Feb 2023