A novel secret image sharing scheme in color images using small shadow images

Hamming Code Strategy for Medical Image Sharing

In medical practice, the scanned image of the patient between the patient and the doctor is confidential. If info is stored on a single server and the server is successfully attacked, it is possible to expose confidential information. Password encryption and data authentication are commonly used to protect patient data, however, encryption and data authentication are computationally expensive and take time to execute on a mobile device. In addition, it is not easy for the patient details related to medical images to leak if the hacked image are not visual.Therefore, in this paper, we propose a way to make medical images remain untouched in this sense. We use our method to quickly create two shadows from two medical images and store them on two servers. Revealing a shadow image does nothing to compromise the confidentiality of a patient’s health. This method is based on Hamming code. With low computational cost, the proposed scheme is suitable for tablet, pamphlets and other mobile devices.

A (k, n)-Threshold Progressive Visual Secret Sharing without Expansion

Visual cryptography (VC) encrypts a secret image into n shares (transparency). As such, we cannot see any information from any one share, and the original image is decrypted by stacking all of the shares. The general (k, n)-threshold secret sharing scheme (SSS) can similarly encrypt and decrypt the original image by stacking at least k (≤ n) shares. If one stack is fewer than k shares, the secret image is unrecognizable. Another subject is progressive visual secret sharing, which means that when more shares are progressively stacked, the combined share becomes clearer. In this study, we constructed an advanced scheme for (k, n)-threshold SSS that can be encrypted in VC for any positive integers n ≥ k ≥ 2 through the method of combination, and the size of each share is the same as that of the original image. That is, no pixel expansion is required. Our scheme is novel, and the results from the theoretical analysis and simulation reveal that our scheme exhibits favorable contrast to that of other related schemes.

A New Visual Multi-Secrets Sharing Scheme by Random Grids

In (2, 2)-visual secret sharing (VSS) schemes, a common type of (k, n)-threshold VSS schemes, secret information can be decoded directly through only two shares by using a human vision system. Several studies have analyzed methods of simplifying the decoding process and refining encoding to pass more secret images through two identical shares. However, limited secret images are retrieved, and the quality of the recovered images is low. This paper proposes an advanced (2, 2)-VSS scheme that can embed N secret images into two rectangular shares. Compared with other related VSS schemes, more secret images can be encrypted and the distortion is adjustable in the proposed scheme, yielding more flexibility in theory and practice.

Significant Secret Image Sharing Scheme Based on Boolean Operation

Traditionally, (k, n) secret image sharing is an approach of breaking down a secret image into n number of shadow images to assign them to n number of users, so that any k or more then k users can bring back the secret image. But in case of less than k, users cannot reveal any partial information about the original image. We have proposed a significant secret image sharing technique based on XOR with arithmetic operations that upgrade the performance of traditional secret image sharing approaches by serving importance to shadow images according to user’s significance. This scheme also conserves the fault tolerance property which plays a vital role in image sharing field.

Improved Secret Image Sharing Scheme in Embedding Capacity without Underflow and Overflow

Computational secret image sharing (CSIS) is an effective way to protect a secret image during its transmission and storage, and thus it has attracted lots of attentions since its appearance. Nowadays, it has become a hot topic for researchers to improve the embedding capacity and eliminate the underflow and overflow situations, which is embarrassing and difficult to deal with. The scheme, which has the highest embedding capacity among the existing schemes, has the underflow and overflow problems. Although the underflow and overflow situations have been well dealt with by different methods, the embedding capacities of these methods are reduced more or less. Motivated by these concerns, we propose a novel scheme, in which we take the differential coding, Huffman coding, and data converting to compress the secret image before embedding it to further improve the embedding capacity, and the pixel mapping matrix embedding method with a newly designed matrix is used to embed secret image data into the cover image to avoid the underflow and overflow situations. Experiment results show that our scheme can improve the embedding capacity further and eliminate the underflow and overflow situations at the same time.