Benefiting from the development of the Internet and smart devices, it is now convenient to transmit images anywhere and anytime, which poses a new challenge for image security. The Visual Cryptography Scheme (VCS) is a secret sharing method for protecting an image without a key, the merit of VCS is the human visual system (HVS) can restore the secret image by simply superimposing qualified shares, without any computation. To eliminate noise-like shares in traditional VCS, this paper presents a novel QR code-based expansion-free and meaningful visual cryptography scheme (QEVCS), which generates visually appealing QR codes for transmitting meaningful shares. When distributing on public networks, this scheme does not attract the attention of potential attackers. By limiting the gray-level of a halftoned image, QEVCS both keep the computation-free of visual cryptography and the size of recovery image same as the secret images. The experimental results show the effectiveness of QEVCS when preserving the privacy of images.
Visual cryptography scheme (VCS) is a secret-sharing scheme which encrypts images as shares and can decrypt shares without digital devices. Although a participant can reveal the secret image by merely stacking a sufficient number of shares, the visual quality of recovered images is reduced, and malicious adversaries can cheat participants by giving faked shares. The paper presents a novel VCS called T-VCS (trusted VCS) which consists of two main components: a high-quality VCS and an enhanced verification scheme of shares based on the emerging Intel Software Guard eXtensions (SGX). While providing high-quality recovery, T-VCS keeps the size of the shares the same as the original secret image. We use SGX to act as a trusted third party (TTP) to verify the validity of the shares in an attested enclave without degrading the image quality. The experimental results show that T-VCS can achieve a balance among contrast, share size, and verification efficiency.
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.
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