Affiliations: [a] Guangxi Key Lab of Multi-Source Information Mining & Security, Guangxi Normal University, Guilin, China
| [b]
Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems, Guilin University of Electronic Technology, Guilin, China
Correspondence:
[*]
Corresponding author. Chunqiang Yu, Guangxi Key Lab of Multi-Source Information Mining & Security, Guangxi Normal University, Guilin 541004, China. E-mail: [email protected].
Abstract: Most data hiding methods have limitations in resisting cropping and noise attacks. Aiming at this problem, a robust data hiding with multiple backups and optimized reference matrix is proposed in this paper. Specifically, secret data is divided into a set of groups and multiple backups of each group data are generated according to the number of backups. The cover image is divided into several blocks. A reference matrix is constructed by four constraints to assist data hiding and data extraction. The proposed method aims to extract exactly at least one backup of each group data so that the correct backups can construct the secret data well if the stego-image is corrupted. Experimental results show that the proposed algorithm is robust to cropping and noise attacks.
Keywords: Data hiding, anti-cropping, anti-noise, multi-backup data, data security
