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High-Capacity Framework for Reversible Data Hiding in Encrypted Image Using Pixel Prediction and Entropy Encoding
IEEE Transactions on Circuits and Systems for Video Technology ( IF 8.3 ) Pub Date : 2022-03-31 , DOI: 10.1109/tcsvt.2022.3163905
Yingqiang Qiu 1 , Qichao Ying 2 , Yuyan Yang 1 , Huanqiang Zeng 1 , Sheng Li 2 , Zhenxing Qian 2
Affiliation  

While the existing reserving room before encryption (RRBE) based reversible data hiding in encrypted image (RDHEI) schemes can achieve decent embedding capacity, the capacity of the existing vacating room by encryption (VRBE) based schemes is relatively low. To address this issue, this paper proposes a generalized framework for high-capacity RDHEI for both the RRBE and VRBE cases. First, an efficient embedding room generation algorithm (ERGA) is designed to produce large embedding room using pixel prediction and entropy encoding. Then, we propose two RDHEI schemes, one for RRBE, another for VRBE. In the RRBE scenario, the image owner generates the embedding room with ERGA and encrypts the preprocessed image using stream cipher with two encryption keys. Then, the data hider locates the embedding room and embeds the additional encrypted data. In the VRBE scenario, the cover image is encrypted by an improved block modulation and permutation encryption algorithm, where the spatial redundancy in the plain-text image is greatly preserved. Then, the data hider applies ERGA on the encrypted image to generate the embedding room and conducts data embedding. For both schemes, receivers with different authentication keys can conduct either error-free data extraction or error-free image recovery. The experimental results show that the two proposed schemes outperform many state-of-the-art RDHEI schemes. Besides, they can ensure high security level, where the original image can be hardly discovered from the encrypted version before or after data hiding by unauthorized users.

中文翻译:


使用像素预测和熵编码在加密图像中隐藏可逆数据的大容量框架



虽然现有的基于加密前预留空间(RRBE)的加密图像中可逆数据隐藏(RDHEI)方案可以实现不错的嵌入容量,但现有的基于加密腾出空间(VRBE)的方案的容量相对较低。为了解决这个问题,本文提出了一个适用于 RRBE 和 VRBE 情况的高容量 RDHEI 通用框架。首先,设计了一种高效的嵌入室生成算法(ERGA),使用像素预测和熵编码来生成大型嵌入室。然后,我们提出了两种 RDHEI 方案,一种用于 RRBE,另一种用于 VRBE。在 RRBE 场景中,图像所有者使用 ERGA 生成嵌入室,并使用具有两个加密密钥的流密码对预处理图像进行加密。然后,数据隐藏者找到嵌入室并嵌入附加的加密数据。在VRBE场景中,通过改进的块调制和排列加密算法对封面图像进行加密,其中明文图像中的空间冗余被大大保留。然后,数据隐藏器对加密图像应用ERGA以生成嵌入空间并进行数据嵌入。对于这两种方案,具有不同认证密钥的接收者可以进行无差错数据提取或无差错图像恢复。实验结果表明,所提出的两种方案优于许多最先进的 RDHEI 方案。此外,它们可以确保高安全级别,在未经授权的用户隐藏数据之前或之后,很难从加密版本中发现原始图像。
更新日期:2022-03-31
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