A secure face recognition scheme based on CKKS homomorphic encryption and neural network

Abstract

Abstract: As big data technology has been evolving over the years, facial recognition is widely used in different fields. However, users are then troubled by safety problems, such as privacy disclosure and data leakage. A face recognition scheme based on homomorphic encryption and neural network under the cloud server is proposed in this paper. The face image is encrypted through the CKKS homomorphic encryption scheme, and the LFW data set is trained through the ResNet50 model and Arcface Loss function in the cloud server, then the vector correlation between the encrypted images is calculated, followed by the decryption of the ciphertext result and comparison with the threshold to judge whether it is the same person, to realize face recognition. The experiment result shows that on the LFW dataset, the scheme of this paper can recognize the cryptograph with an accuracy rate of 99.398% when the threshold value is about 0.25. This result proves the proposed scheme has high recognition accuracy.

Key words: cloud computing, face recognition, homomorphic encryption, neural network

CLC Number:

TP391

SU Yun-xuan, TU Zheng, WANG Xu-an, LIN Chuan. A secure face recognition scheme based on CKKS homomorphic encryption and neural network[J]. Journal of Lanzhou University of Technology, 2023, 49(2): 103-109.

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