A Novel (2, 3)-Threshold Reversible Secret Image Sharing Scheme Based on Optimized Crystal-Lattice Matrix

Abstract

The (k, n)-threshold reversible secret image sharing (RSIS) is technology that conceals the secret data in a cover image and produces n shadow versions. While k (k ≤ n) or more shadows are gathered, the embedded secret data and the cover image can be retrieved without any error. This article proposes an optimal (2, 3) RSIS algorithm based on a crystal-lattice matrix. Sized by the assigned embedding capacity, a crystal-lattice model is first generated by simulating the crystal growth phenomenon with a greedy algorithm. A three-dimensional (3D) reference matrix based on translationally symmetric alignment of crystal-lattice models is constructed to guide production of the three secret image shadows. Any two of the three different shares can cooperate to restore the secret data and the cover image. When all three image shares are available, the third share can be applied to authenticate the obtained image shares. Experimental results prove that the proposed scheme can produce secret image shares with a better visual quality than other related works.

Asymmetric Orientation Combination for Reversible and Authenticable Data Hiding of Dual Stego-images

“…The authentication capability of a tampered shadow to be detected by a faithful shadow is another concern of the secret sharing approaches [24][25][26][27][28]. In 2007, Yang et al [24] proposed a secret sharing scheme with authentication.…”

“…In 2020, Gao et al [27] proposed a (2, 3)-threshold secret sharing scheme with an authentication mechanism, which can detect 90% of tampered pixels. The next year, Lin et al [28] proposed a crystal lattice matrix for the same secret sharing scheme. Based on the new matrix, the detection rate of tampered pixels is increased to 99%.…”

Multilayer Reversible Information Hiding with Prediction-Error Expansion and Dynamic Threshold Analysis

“…The word "reversible" in this context indicates that one can remove the embedded data to restore the original image. In recent years, numerous principles of the reversible information hiding technology were proposed, such as the difference expansion method [3][4][5][6], histogram method [7][8][9][10][11], difference of the pixel value method [12][13][14], the least significant bit method (LSB) [15,16], dual-image-based schemes [17,18], other reversible information hiding schemes [19][20][21][22][23][24][25], and the predictionerror method [26][27][28][29][30][31][32]. A good information hiding theory provides a significant capacity for embedded secret data that cannot be detected [1,33,34].…”