Analysis and Design of Secure Visual Secret Sharing Schemes with Enhanced Contrast

Abstract

The Visual Secret Sharing (VSS) scheme is a cryptography technique, which divides the secret image into multiple shares. These shares are then transmitted over a network to respective participants. To recover the secret image, all participants must have to stack their shares together at the receiver end. Naor and Shamir (1994a) first proposed basic VSS scheme for binary images using threshold scheme. The scheme generated shares with increased sizes, hence it suffered from the problem of expanded share. To overcome the problem of expanded shares, Block-based Progressive Visual Secret Sharing (BPVSS) scheme was proposed by Hou et al. (2013a). BPVSS is an effective scheme suitable for both gray-scale and color images. Although BPVSS scheme recovered secret image with better quality, it still suffers from the problems like 1) The restored image obtained by joining all the shares together always results in a binary image. 2) The maximum contrast achievable by BPVSS is 50%. This thesis presents various mechanisms to improve reconstruction quality and the contrast of a secret image transmitted using BPVSS. First technique proposed by thesis is Randomised Visual Secret Sharing (RVSS) (Mhala et al. 2018). The RVSS is an encryption technique that utilises block-based progressive visual secret sharing and Discrete Cosine Transform (DCT) based reversible data embedding technique to recover a secret image. The recovery method is based on progressive visual secret sharing, which recovers the secret image block by block. The existing block based schemes achieve the highest contrast level of 50% for noise-like and meaningful shares. The presented scheme achieves a contrast level of 70-90% for noise-like and 70-80% for meaningful shares. The enhancement of contrast is achieved by embedding additional information in the shares using DCT-based reversible data embedding technique. Experimental results showed that the proposed scheme restores the secret image with better visual quality in terms of human visual system based parameters Although RVSS scheme recovers secret images with a better contrast; the scheme still suffers from the problems of blocking artifacts. To further improve the reconstruction quality of the RVSS, this thesis presents a novel Super-resolution based Visual Secret Sharing (SRVSS) technique. The SRVSS scheme used super-resolution concept along with data hiding technique to improve the contrast of the secret images. The experimental results showed that the SRVSS scheme achieves the contrast of 70-80% for meaningful shares and 99% for noise-like shares. Also, scheme recovers the secret image free from blocking artifacts. Nowadays, medical information is being shared over the communication networks due to ease of technology. The patient’s medical information has to be securely communicated over a network for Computer Aided Diagnosis (CAD). Most of the communication networks are prone to attacks from an intruder thus compromising the security of patients data. Therefore, there is a need to transmit medical images securely over a network. Visual secret sharing scheme can be used to transmit the medical images over a network securely. This thesis has applied the super-resolution based VSS scheme on the medical images to transmit them over a network. The experimental results showed that, scheme recovers medical images with better contrast. The experimental results showed that the presented system is able to reconstruct the secret image with the contrast of almost 85-90% and similarity of almost 77%. Additionally, the performance of the presented system is evaluated using the existing CAD systems. The reconstructed images using the presented super-resolution based VSS scheme achieves the similar classification accuracy as that of existing CAD system. Nowadays, underwater images are being used to identify various important resources like objects, minerals, and valuable metals. Due to the wide availability of the Internet, the underwater images can be transmitted over a network. As underwater images contain important information, there is a need to transmit them securely over a network. Visual secret sharing (VSS) scheme is a cryptographic technique, which is used to transmit visual information over insecure networks. Randomized VSS (RVSS) scheme recovers Secret Image (SI) with a Self-Similarity index (SSIM) of 60-80%. But, RVSS is suitable for general images, whereas underwater images are more comii plex than general images. The work presented in the thesis to share underwater images over a network uses a super-resolution based VSS scheme. Additionally, it has removed blocking artifacts from the reconstructed secret image using Convolution Neural Network (CNN)-based architecture. The presented CNN-based architecture uses a residue image as a cue to improve the visual quality of the SI. The experimental results show that the presented VSS scheme can reconstruct SI with almost 86-99% SSIM. Hence can be used to transmit complex images over a insecure channels.