Visual cryptography

About: Visual cryptography is a research topic. Over the lifetime, 1724 publications have been published within this topic receiving 25300 citations.

A New Simple Non-Expansion Algorithm for (2,2) - Visual Secret Sharing Scheme

Abstract: Visual cryptography (VC) is a powerful encryption technique which combines perfect secrecy and secret sharing in cryptography with respect to images. VC takes a binary image (the secret) and divides it into two or more pieces known as shares (transparencies). When the shares are superimposed, the secret can be recovered. One of the distinguishing features of VC is that it needs no computational power for decryption. All what VC needs for decryption is the human visual system (the human eye). Two main factors affect the quality of a visual cryptography scheme; the pixel expansion and the contrast. In this papers we propose a new simple non-expansion algorithm for (2,2)-visual secret sharing scheme (VSS). The shares produced by this algorithm and the reconstructed image are not expanded in size, and all have the same size as the original (secret) image. It encodes the original (secret) image a 4-pixel blockwise to 4-pixel blocks in each share.

Visual Cryptography for Compressed Sensing of Images with Transmission over Multiple Channels

Abstract: Visual cryptography is an effective means for ownership protection of multimedia contents. Due to the massive amount of multimedia contents, compression is an inevitable part before transmission over channels. Recently, compressed sensing has attracted much attention with its superior performance in data compression. With compressed sensing, few amounts of coefficients are able to obtain reconstructed image with acceptable quality. In order to protect the ownership of multimedia contents with compressed sensing, we hide visual cryptography information, or shares, into compressed sensing coefficients. Besides, considering the characteristics of visual cryptography, compressed sensing coefficients are split into chunks for delivering over multiple channels. After reception, extracted shares can be verified to protect the ownership. Simulation results have pointed out that our method can be applicable, and integration with robust visual cryptography may lead to enhanced performances.

Multiple Secrets Sharing with Meaningful Shares

Abstract: Traditional Visual Cryptography method produces random shares which is susceptible to attackers Some methods have been proposed to generate innocent-looking shares so that attacker cannot get doubtful by looking at the random pattern of the share They look like a valid image and the adversary cannot judge whether it is a secret share or not However many of them use additional data structure and take much time in encoding the secret In this paper, we propose a method which produces meaningful shares for color images without the need of any additional data structure and takes less time for encoding The share size does not vary with the number of colors present in the secret image The method is further extended to share multiple secrets together to reduce the overhead of keeping too many shares

Meaningful Secret Image Sharing with Saliency Detection

Abstract: Secret image sharing (SIS), as one of the applications of information theory in information security protection, has been widely used in many areas, such as blockchain, identity authentication and distributed cloud storage. In traditional secret image sharing schemes, noise-like shadows introduce difficulties into shadow management and increase the risk of attacks. Meaningful secret image sharing is thus proposed to solve these problems. Previous meaningful SIS schemes have employed steganography to hide shares into cover images, and their covers are always binary images. These schemes usually include pixel expansion and low visual quality shadows. To improve the shadow quality, we design a meaningful secret image sharing scheme with saliency detection. Saliency detection is used to determine the salient regions of cover images. In our proposed scheme, we improve the quality of salient regions that are sensitive to the human vision system. In this way, we obtain meaningful shadows with better visual quality. Experiment results and comparisons demonstrate the effectiveness of our proposed scheme.