Abstract
Face recognition is playing an increasingly important role in present society, and suffers from the privacy leakage in plaintext. Therefore, a recognition system based on homomorphic encryption that supports privacy preservation is designed and implemented in this paper. This system uses the CKKS algorithm in the SEAL library, latest homomorphic encryption achievement, to encrypt the normalized face feature vectors, and uses the FaceNet neural network to learn on the image’s ciphertext to achieve face classification. Finally, face recognition in ciphertext is accomplished. After been tested, the whole process of extracting feature vectors and encrypting a face image takes only about 1.712s in the developed system. The average time to compare a group of images in ciphertext is about 2.06s, and a group of images can be effectively recognized within 30 degrees of face bias, with a recognition accuracy of 96.71%. Compared to the face recognition scheme based on the Advanced Encryption Standard encryption algorithm in ciphertext proposed by Wang et al. in 2019, our scheme improves the recognition accuracy by 4.21%. Compared to the image recognition scheme based on the Elliptical encryption algorithm in ciphertext proposed by Kumar S et al. in 2018, the total spent time in our system is decreased by 76.2%. Therefore, our scheme has better operational efficiency and practical value while ensuring the users’ personal privacy. Compared to the face recognition systems in plaintext presented in recent years, our scheme has almost the same level on recognition accuracy and time efficiency.
Highlights
As an important part of artificial intelligence, face recognition is widely used from hotelBeijing Electronics Science and Technology Institute, Beijing100070, China 2 School of Telecommunication Engineering, Xidian University, Xi’an710071, China check-in to mobile payment, and has become an indispensable way of identity authentication in modern life
A fully homomorphic encryption (FHE) scheme based on the ideal lattice was proposed by Gentry[2] in 2009, which has attracted great attention from cryptographers all over the world
We briefly introduce the homomorphic encryption algorithm and FaceNet architecture, and introduce the data set and development tools used in the test
Summary
As an important part of artificial intelligence, face recognition is widely used from hotel. The ciphertext is irregular and difficult to operate, which limits the application range of traditional encryption algorithms To address this problem, the concept of homomorphic encryption was proposed by Rivest et al.[1] in 1978. In order to solve this problem, we combine homomorphic encryption with face recognition in this paper, which can provide security for data, and provide privacy preservation for users. A face recognition scheme in ciphertext is proposed based on SEAL library in this paper. This system has better application prospects and development prospects than the face recognition system in plaintext. (1) A face recognition scheme based on SEAL library in ciphertext is proposed for the first time.
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