Reversible Data Hiding in Encrypted Images With Secret Sharing and Hybrid Coding

Abstract

Reversible data hiding in encrypted images (RD-HEI) is an essential data security technique. Most RDHEI methods cannot perform well in embedding capacity and security. To address this issue, we propose a new RDHEI method using Chinese remainder theorem-based secret sharing (CRTSS) and hybrid coding. Specifically, a hybrid coding is first proposed for RDH to achieve high embedding capacity. At the content owner side, a novel iterative encryption is designed to conduct block based encryption for perfectly preserving the spatial correlation of original blocks in their encrypted blocks. Then, the CRTSS with the constraints is exploited to generate multiple encrypted image shares, in which spatial correlations of the encrypted blocks are also preserved. Meanwhile, the CRTSS provides good security properties for the proposed method. Since there are strong spatial correlations in the blocks of each share, the datahider can exploit the proposed hybrid coding to perform data embedding for improving capacity. On the receiver side, even if some shares are corrupted/missing, the original image can be losslessly recovered as long as enough uncorrupted marked shares are obtained. Experiment results show that the proposed RDHEI method outperforms some state-of-the-art methods, including some secret sharing (SS) based methods in terms of embedding capacity.

Secure Image Sharing: Innovating Encryption and Concealment Methods

“…The prediction value of a block's pixel pi,j is determined as in where b = p(i−1, j), c = p(i−1, j −1), and a = p(i, j −1). [55] The median edge detector (MED) predicts the remaining pixels, while the preorder pixels of the first row or column anticipate the remaining pixels. Keep in mind that the reference pixel, p1,1, is not included in the data concealing.…”

“…Keep in mind that the reference pixel, p1,1, is not included in the data concealing. Following that, the prediction error (PE) is produced by [55] Each block's PEs are computed using Equation ( 2), and they are then converted into the one-dimensional PE sequence e = [e2, e3,..., ef ] (f = t×t) in the order shown in Figure 1. The PEs' indexes in the one-dimensional sequence are represented by the numbers in Fig.…”

“…Hierarchical Structure. [55] In this work, the payload gain determines whether me with 2q−1<me<2q returns the upper layer or not. For each |ei|(2≤i≤f) in the block where 2q−1<me<2q, there are three possible outcomes: |ei|∈[0,2q−1−1], |ei|=2q−1, and |ei|∈[2q−1+1,2q−1]; these three situations can hold 8−q, 8−q−1, and 8−q secret bits, respectively, in accordance with the approach [31].…”

“…2, when me with 2q−1<me<2q is situated on the (8−q )th layer, the block's payload is where n 0 +n 1 +n 2 +n 3 = f − 1. [55] It is important to note that C2's payload is the same whether it is in the (8−q−1) th layer or the (8−q) th layer. Consequently, in contrast to the (8−q−1) th layer, the block's (8−q) th layer's payload gain is ECg=ECp−EC = n 0 +n 1 +n 3…”

An n-Dimensional Chaotic Map with Application in Reversible Data Hiding for Medical Images

“…The security of the concealment mechanism is guaranteed by the key-based encryption scheme. Based on the Chinese residue theorem, Yu et al [ 20 ] present a new method for hybrid encoding and secret sharing. In particular, a revolutionary iterative encryption is aimed to precisely preserve the spatial correlation of the original block in its encryption block, whereas a hybrid encoding aims to achieve high embedding capacity.…”