mlsanityData to 7 Oct 2026

OTB-morph: One-Time Biometrics via Morphing

arXiv 2302.09053 ↗First posted 17 Feb 2023cs.LG cs.CR cs.CVcited by 5

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Abstract (arXiv)

Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in biometric recognition systems. This transformation is repeatable enabling subsequent biometric comparisons. This paper is introducing a new idea to exploit as a transformation function for cancelable biometrics aimed at protecting the templates against iterative optimization attacks. Our proposed scheme is based on time-varying keys (random biometrics in our case) and morphing transformations. 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 5 papers in the map (data through 7 Oct 2026). Builds on 12 of its 57 references that are in the map. First posted on arXiv 17 Feb 2023.

Builds on

12 of 57 references.

References · 12

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2019Deep Leakage from Gradientscited by 1,004
  3. 2017VGGFace2: A dataset for recognising faces across pose and agecited by 911
  4. 2014Learning Face Representation from Scratchcited by 451
  5. 2022AdaFace: Quality Adaptive Margin for Face Recognitioncited by 390
  6. 2020Face Morphing Attack Generation & Detection: A Comprehensive Surveycited by 63
  7. 2019GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detectioncited by 42
  8. 2017Deep Supervised Discrete Hashingcited by 36
  9. 2020DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representationscited by 26
  10. 2022Facial Soft Biometrics for Recognition in the Wild: Recent Works, Annotation, and COTS Evaluationcited by 19
  11. 2016Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detectioncited by 8
  12. 2021OTB-morph: One-Time Biometrics via Morphing applied to Face Templatescited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 0; 2025: 2; 2026: 1.

5 papers.

  1. 2023Blockchain and Biometrics: Survey, GDPR Analysis, and Future Directionscited by 1
  2. 2025FaceAnonyMixer: Cancelable Faces via Identity Consistent Latent Space Mixingcited by 1
  3. 2023Optimizing Key-Selection for Face-based One-Time Biometrics via Morphingcited by 0
  4. 2025NLML-HPE: Head Pose Estimation with Limited Data via Manifold Learningcited by 0
  5. 2026Binding Biometrics with AI Agent Identifiers for Delegation of Authoritycited by 0