Privacy-preserving face recognition method based on extensible feature extraction

Weitong Hu, Di Zhou, Zhenxin Zhu, Tong Qiao, Ye Yao, Mahmoud Hassaballah

Abstract: Highlights•In the proposed framework of PPFR, the accuracy of face recognition remains as high as we expect regardless of in the plaintext or encrypted domain.•The feature extraction component can be customized to meet specific requirements by selecting different baseline models, such as MobileFaceNet, ResNet-18, and ResNet-50.•The proposed PPFR solution outperforms the baseline frameworks in terms of data transmission volume, computational efficiency, and recognition accuracy.