计算机科学
加密
信息隐藏
可分离空间
人工智能
模式识别(心理学)
计算机视觉
算法
数据挖掘
计算机安全
理论计算机科学
图像(数学)
数学
数学分析
作者
Bing Chen,Wei Lu,Jiwu Huang,Jian Weng,Yicong Zhou
标识
DOI:10.1109/tdsc.2020.3011923
摘要
The existing models of reversible data hiding in encrypted images (RDH-EI) are based on single data-hider, where the original image cannot be reconstructed when the data-hider is damaged. To address this issue, this article proposes a novel model with multiple data-hiders for RDH-EI based on secret sharing. It divides the original image into multiple different encrypted images with the same size of the original image and distributes them to multiple different data-hiders for data hiding. Each data-hider can independently embed data into the encrypted image to obtain the corresponding marked encrypted image. The original image can be losslessly recovered by collecting sufficient marked encrypted images from undamaged data-hiders when individual data-hiders are subjected to potential damage. This further protects the security of the original image. We provide four cases of the proposed model, namely, two joint cases and two separable cases. From the proposed model, we derive a separable RDH-EI method with high-capacity. Experimental results are presented to illustrate the effectiveness of the proposed method.
科研通智能强力驱动
Strongly Powered by AbleSci AI