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Updated: Sep 15, 2025

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A cryptosystem for face recognition based on optical interference and phase truncation theory.

Yuan Guo1, Ping Zhai2, Debao Jia2

  • 1Department of Computer Science and Technology, Heilongjiang University, Harbin, 150080, China. guoyuan171@126.com.

Scientific Reports
|July 14, 2025
PubMed
Summary
This summary is machine-generated.

This study presents a novel optical cryptosystem for secure facial image transmission and storage. The system uses Amplitude-Phase Separation Asynchronous Encryption (APSAE) for enhanced privacy and efficient face recognition.

Keywords:
CryptosystemDual keyFace recognitionInterferencePhase truncation

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Area of Science:

  • Computer Science
  • Cryptography
  • Biometrics

Background:

  • Facial recognition technology is widespread, but securing facial image data is challenging due to privacy concerns.
  • Existing encryption methods may not adequately protect sensitive biometric data.

Purpose of the Study:

  • To develop an innovative cryptosystem for secure facial image encryption, transmission, and storage.
  • To enable secure face recognition on decrypted images using deep learning.

Main Methods:

  • Utilized optical interference and phase truncation theory for image encryption.
  • Implemented a dual-key mechanism for flexible decryption.
  • Introduced Amplitude-Phase Separation Asynchronous Encryption (APSAE) to address vulnerabilities.
  • Employed deep learning for face recognition on decrypted images.

Main Results:

  • Achieved a face recognition accuracy of [Formula: see text] on the LFW dataset.
  • Demonstrated efficient encryption (40.47 s for 10,000 images) and decryption (0.02 s per image).
  • Showcased strong resistance to attacks with high computational efficiency.

Conclusions:

  • The proposed cryptosystem effectively addresses facial image privacy leakage.
  • It offers a secure and efficient solution for biometric recognition systems.
  • This research advances secure data handling in the field of biometrics.