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Artificial Intelligence-Enabled Facial Privacy Protection for Ocular Diagnosis: Development and Validation Study.

Haizhu Tan1, Hongyu Chen2,3, Zhenmao Wang4

  • 1Department of Preventive Medicine, Shantou University Medical College, 22 Xinling Rd, Shantou, 515031, China, 86 13318055534.

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|July 9, 2025
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Summary

Digital FaceDefender, an AI solution, safeguards facial biometric data privacy while enabling auxiliary diagnoses. It significantly reduces reidentification risk, balancing security with clinical utility.

Keywords:
Digital FaceDefenderartificial intelligenceauxiliary diagnosisfacial biometric dataocular diseaseprivacy protection

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Area of Science:

  • Computer Science
  • Biomedical Engineering
  • Data Privacy

Background:

  • Facial biometric data offers clinical value but presents significant privacy and security risks.
  • Protecting sensitive facial data is crucial for its ethical use in healthcare.

Purpose of the Study:

  • To develop an AI-driven solution, Digital FaceDefender, for safeguarding facial biometric data privacy.
  • To support auxiliary diagnostic functions while mitigating reidentification risks.

Main Methods:

  • Synthesized diverse Asian face avatars and extracted landmark data.
  • Applied affine transformations, color correction, and Gaussian blur for image enhancement.
  • Assessed reidentification risk using ArcFace and established diagnostic benchmarks via Cohen Kappa analysis.

Main Results:

  • Digital FaceDefender significantly reduced facial similarity scores and reidentification accuracy across various poses.
  • Established diagnostic benchmarks showed moderate agreement with ophthalmologists' assessments.
  • A user-friendly Digital FaceDefender platform is now available.

Conclusions:

  • Digital FaceDefender effectively balances facial data privacy protection with diagnostic application needs.
  • The developed benchmarks support reliable auxiliary diagnoses.
  • The solution offers a practical approach to managing facial biometric data security.