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基于像素值排序和秘密共享的多数据隐藏器加密图像无损可逆数据隐藏。

Lossless Reversible Data Hiding in Encrypted Image for Multiple Data Hiders Based on Pixel Value Order and Secret Sharing.

机构信息

School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Beijing Electronic Science and Technology Institute, Beijing 100070, China.

出版信息

Sensors (Basel). 2023 May 18;23(10):4865. doi: 10.3390/s23104865.

DOI:10.3390/s23104865
PMID:37430779
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10222064/
Abstract

Reversible data hiding in encrypted images (RDH-EI) is instrumental in image privacy protection and data embedding. However, conventional RDH-EI models, involving image providers, data hiders, and receivers, limit the number of data hiders to one, which restricts its applicability in scenarios requiring multiple data embedders. Therefore, the need for an RDH-EI accommodating multiple data hiders, especially for copyright protection, has become crucial. Addressing this, we introduce the application of Pixel Value Order (PVO) technology to encrypted reversible data hiding, combined with the secret image sharing (SIS) scheme. This creates a novel scheme, PVO, Chaotic System, Secret Sharing-based Reversible Data Hiding in Encrypted Image (PCSRDH-EI), which satisfies the (k,n) threshold property. An image is partitioned into shadow images, and reconstruction is feasible when at least shadow images are available. This method enables separate data extraction and image decryption. Our scheme combines stream encryption, based on chaotic systems, with secret sharing, underpinned by the Chinese remainder theorem (CRT), ensuring secure secret sharing. Empirical tests show that PCSRDH-EI can reach a maximum embedding rate of 5.706 bpp, outperforming the state-of-the-art and demonstrating superior encryption effects.

摘要

在加密图像中的可逆数据隐藏 (RDH-EI) 在图像隐私保护和数据嵌入方面起着重要作用。然而,传统的 RDH-EI 模型,涉及图像提供者、数据隐藏者和接收者,将数据隐藏者的数量限制为一个,这限制了它在需要多个数据嵌入者的场景中的适用性。因此,需要一种能够容纳多个数据隐藏者的 RDH-EI,特别是用于版权保护,这已经变得至关重要。为了解决这个问题,我们将像素值排序 (PVO) 技术应用于加密可逆数据隐藏,并结合秘密图像共享 (SIS) 方案。这创建了一种新的方案,即 PVO、混沌系统、基于秘密共享的加密图像可逆数据隐藏 (PCSRDH-EI),满足 (k,n) 门限特性。图像被分割成 影子图像,当至少有 影子图像时可以进行重建。这种方法可以实现单独的数据提取和图像解密。我们的方案结合了基于混沌系统的流加密和秘密共享,秘密共享基于中国剩余定理 (CRT),确保了安全的秘密共享。实验结果表明,PCSRDH-EI 可以达到 5.706 bpp 的最大嵌入率,优于最新技术,并显示出优越的加密效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/9fe54efd977d/sensors-23-04865-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/0a3e7a20b5fa/sensors-23-04865-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/34661d51a921/sensors-23-04865-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/442b87fb1cd3/sensors-23-04865-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/51dd82251b57/sensors-23-04865-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/1e17f3034ba2/sensors-23-04865-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/0a050605d516/sensors-23-04865-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/54aea1c48701/sensors-23-04865-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/e827d0eed087/sensors-23-04865-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/630e696469e9/sensors-23-04865-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/8fc8f7efa362/sensors-23-04865-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/9fe54efd977d/sensors-23-04865-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/0a3e7a20b5fa/sensors-23-04865-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/6204321aa8ba/sensors-23-04865-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/9f0b0b5198b7/sensors-23-04865-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/34661d51a921/sensors-23-04865-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/442b87fb1cd3/sensors-23-04865-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/51dd82251b57/sensors-23-04865-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/1e17f3034ba2/sensors-23-04865-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/0a050605d516/sensors-23-04865-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/54aea1c48701/sensors-23-04865-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/e827d0eed087/sensors-23-04865-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/630e696469e9/sensors-23-04865-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/8fc8f7efa362/sensors-23-04865-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bb/10222064/9fe54efd977d/sensors-23-04865-g013.jpg

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本文引用的文献

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Reversible Data Hiding in Encrypted Image Using Multiple Data-Hiders Sharing Algorithm.基于多数据隐藏者共享算法的加密图像可逆数据隐藏
Entropy (Basel). 2023 Jan 21;25(2):209. doi: 10.3390/e25020209.
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Suggested Integral Analysis for Chaos-Based Image Cryptosystems.基于混沌的图像密码系统的建议积分分析。
Entropy (Basel). 2019 Aug 20;21(8):815. doi: 10.3390/e21080815.
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