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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2300750


A reversible data hiding in encrypted image based on additive secret sharing and adaptive joint coding using an intelligent predictor


Author(s):  Ziyi ZHOU, Chengyue WANG, Kexun YAN, Hui SHI, Xin PANG

Affiliation(s):  School of Computer Science and Artificial Intelligence, Liaoning Normal University, Dalian 116029, China

Corresponding email(s):   shihui_jiayou@lnnu.edu.cn

Key Words:  Reversible data hiding in encrypted images (RDHEIs), Additive secret sharing, Adaptive joint coding, Intelligent predictor


Ziyi ZHOU, Chengyue WANG, Kexun YAN, Hui SHI, Xin PANG. A reversible data hiding in encrypted image based on additive secret sharing and adaptive joint coding using an intelligent predictor[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300750"
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Abstract: 
reversible data hiding in encrypted images (RDHEIs) is essential for safeguarding sensitive information within the encrypted domain. In this study, we propose an intelligent pixel predictor based on a residual group block and a spatial attention module, showcasing superior pixel prediction performance compared to existing predictors. Additionally, we introduce an adaptive joint coding method that leverages bit-plane characteristics and intra-block pixel correlations to maximize embedding space, outperforming single coding approaches. The image owner employs the presented intelligent predictor to forecast the original image, followed by encryption through additive secret sharing before conveying it to data hiders. Subsequently, data hiders encrypt secret data and embed them within the encrypted image before transmitting it to the receiver. The receiver can extract secret data and recover the original image losslessly, with the processes of data extraction and image recovery being separable. Our innovative approach combines an intelligent predictor with additive secret sharing, achieving reversible data embedding and extraction while ensuring security and lossless recovery. Experimental results demonstrate that the predictor performs well and has a substantial embedding capacity. For the Lena image, our predictor achieved a prediction error within the range of [-5, 5] 242,500 times and an embedding capacity of 4.39bpp.

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