Privacy Preserving Encoder Classifier for Access Control Based on Face Recognition

• Published in: 2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA) pp. 1 - 5
• Main Authors: El Saj, Raghida, Pham, Chi-Hieu, Gooya, Ehsan Sedgh, Alfalou, Ayman, Khalil, Mohamad
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16-10-2023
• Subjects: Access control; Data privacy; Discrete cosine transforms; Encryption; Face recognition; generated output-based classifier; Image recognition; privacy preserving; Process control
• ISSN: 2154-512X
• DOI: 10.1109/IPTA59101.2023.10320056

Processing private data to control the access of a system by identifying users and blocking unknowns is becoming increasingly important and requires the development of a privacy-preserving approach. This article presents a privacy-preserving access control method based on facial recognition. This method highlights the performance of classifiers based on generated output. A classifier based on generated output, a ResNet encoder, was used and tested on both clear data and encrypted data. The private data, the face images, were encrypted using a new perceptual image encryption method based on the discrete cosine transform.