Reversible Data Hiding in Shared Images with Separate Cover Image Reconstruction and Secret Extraction
Document Type
Article
Publication Date
1-1-2024
Abstract
Reversible data hiding is widely utilized for secure communication and copyright protection. Recently, to improve embedding capacity and visual quality of stego-images, some Partial Reversible Data Hiding (PRDH) schemes are proposed. But these schemes are over the plaintext domain. To protect the privacy of the cover image, Reversible Data Hiding in Encrypted Images (RDHEI) techniques are preferred. In addition, the full separability of cover image reconstruction and data restoration is also an important characteristic that cannot be achieved by most RDHEI schemes. To solve the issues, a partial and a complete Reversible Data Hiding in Shared Images with Separate Cover Image Reconstruction and Secret Extraction (RDHSI-SRE) are proposed in this paper. In the proposed schemes, the secret data is divided by Secret Sharing (SS). Then, the marked shared images are generated based on the proposed modify-and-recalculate strategy. The receiver can extract embedded data and reconstruct the image separably using k-out-of-n marked shared images. In the embedding phase of partial RDHSI-SRE (PRDHSI-SRE), the pixel values are modified according to the proposed Minimizing-Square-Errors Strategy to achieve high visual quality, and the complete RDHSI-SRE (CRDHSI-SRE) embeds data by modifying random coefficients to achieve reversibility. The experimental results and theoretical analyses demonstrate that the proposed schemes have a high embedding performance. Most importantly, the proposed schemes are fault-tolerant and completely separable.
Identifier
85182367401 (Scopus)
Publication Title
IEEE Transactions on Cloud Computing
External Full Text Location
https://doi.org/10.1109/TCC.2024.3351143
e-ISSN
21687161
First Page
186
Last Page
199
Issue
1
Volume
12
Recommended Citation
Xiong, Lizhi; Han, Xiao; Yang, Ching Nung; and Shi, Yun Qing, "Reversible Data Hiding in Shared Images with Separate Cover Image Reconstruction and Secret Extraction" (2024). Faculty Publications. 1114.
https://digitalcommons.njit.edu/fac_pubs/1114