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    基于颜色通道关联性和熵编码的彩色密文图像可逆信息隐藏

    Reversible Data Hiding in Color Encrypted Images Based on Color Channels Correlation and Entropy Coding

    • 摘要: 随着云计算领域数据安全和用户隐私的需求发展,密文图像可逆信息隐藏技术(reversible data hiding in encrypted images,RDHEI)已经越来越受到人们的关注,但目前大多数的密文图像可逆信息隐藏都是基于灰度图像,它们与彩色图像相比在应用场景上有很大局限性. 此外,由于目前关于密文域的可逆信息隐藏方法主要集中于灰度图像,同时针对彩色图像的特性优化较少,往往无法对彩色载体图像实现更好的性能,所以进一步加强对基于彩色密文图像的可逆信息隐藏算法的研究具有很高的价值. 首次提出了一种可以用于云计算环境的基于颜色通道相关性和熵编码的高性能彩色密文图像可逆信息隐藏算法(RDHEI-CE). 首先,原始彩色图像的RGB通道被分离并分别得出预测误差. 接下来,通过自适应熵编码和预测误差直方图生成嵌入空间,之后通过颜色通道相关性进一步扩展嵌入空间,并将秘密信息嵌入加密图像中. 最后,对载密图像进行可逆置乱以抵御唯密文攻击. 与大多数最先进的可逆信息隐藏方法相比,实验表明RDHEI-CE算法提供了更高的嵌入率和更好的安全性,并且拓宽了可逆信息隐藏在云端的应用场景.

       

      Abstract: With the continuous development of cloud computing technology, the reversible data hiding in encrypted images (RDHEI) has received more and more attention. But most of the reversible data hiding in encrypted images are based on grey-scale, which have great limitations in application scenario compared to color images. Moreover, since the current reversible data hiding methods in the encrypted domain mainly focus on grayscale images, and there are few optimizations for the characteristics of color images, it is hard to obtain better performance by applying these algorithms, so it is of high value to further investigate the reversible data hiding algorithm in color encrypted images. In this paper, we propose a high-performance RDHEI of color images algorithm for the first time based on color channels correlation and entropy encoding (RDHEI-CE) for cloud computing. First, the RGB channels of the color image are separated and the prediction errors are derived separately. Next, the embedding space is generated by adaptive entropy encoding and prediction errors histogram. The correlation between color channels is then used to further expand the embedding space and embed secret message on the encrypted image. Finally, the marked encrypted image must be scrambled in order to resist a ciphertext-only attack. Compared to most state-of-the-art RDHEI methods, experimental results show that the RDHEI-CE method provides a greater embedding rate and better security and broadens the application scene of reversible data hiding in the cloud.

       

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