A Privacy-Preserving Biometric Recognition System with Visual Cryptography

Abstract

The popularity of more powerful and smarter digital devices has improved the quality of life and poses new challenges to the privacy protection of personal information. In this paper, we propose a biometric recognition system with visual cryptography, which preserves the privacy of biometric features by storing biometric features in separate databases. Visual cryptography combines perfect ciphers and secret sharing in cryptography with images, thus eliminating the complex operations in existing privacy-preserving schemes based on cryptography or watermarking. Since shares do not reveal any feature about biometric information, we can efficiently transmit sensitive information among sensors and smart devices in plain. To abate the influence of noise in visual cryptography, we leverage the generalization ability of transfer learning to train a visual cryptography-based recognition network. Experimental results show that our proposed method keeps the high accuracy of the feature recognition system when providing security.