Separable and Reversible Data Hiding in Encrypted Images using Parametric Binary Tree Labeling
This paper first introduces a parametric binary tree labeling scheme (PBTL) to label image pixels in two different categories. Using PBTL, a data embedding method (PBTL-DE) is proposed to embed secret data to an image by exploiting spatial redundancy within small image blocks. We then apply PBTL-DE into the encrypted domain and propose a PBTLbased reversible data hiding method in encrypted images (PBTLRDHEI). PBTL-RDHEI is a eparable and reversible method that both the original image and secret data can be recovered and extracted losslessly and independently. Experiment results and analysis show that PBTL-RDHEI is able to achieve an average embedding rate as large as 1.752 bpp and 2.003 bpp when block size is set to 2 _ 2 and 3 _ 3, respectively
Existing RDHEI methods can be classified into three categories, namely reserving room before encryption (RRBE) reserving room after encryption (RRAE) and vacating room by encryption (VRBE. The RRBE methods use some traditional RDH methods or exploit spatial redundancy from the original image to reserve spare room before image encryption. The second category mainly uses the standard image encryption algorithms such as AES, RC4 or homomorphic encryption to encrypt the original image directly. The VRBE methods adopt some specific encryption algorithm to encrypt the original image while keeping spatial redundancy in the encrypted image so that it can be exploited for data embedding. Ma et al. first proposed a RRBE method. They divide the original image into smooth area and coarse area, and embed several least significant bit (LSB) planes of the coarse area into the smooth area using the traditional RDH method . The reserved LSB planes are then used for data embedding. Mathew et al.
We propose a parametric binary tree labeling scheme (PBTL) to label pixels in two different categories. Selecting different settings of parameters, PBTL will provide different pixel labeling strategies. Using PBTL, we propose a data embedding algorithm (PBTL-DE). It exploits spatial redundancy in small image blocks and embeds secret data into cover images using pixel labeling and bit replacement. Different from the traditional data embedding methods that embed secret data by modifying the plaintext cover image pixel values in an imperceptive way, PBTL-DE is designed for encrypted images. Thus, the significant changes to pixel values are acceptable. Based on PBTL-DE algorithm, we further propose a PBTL-based RDHEI method (PBTL-RDHEI). Simulation results of applying PBTL-RDHEI to 1000 randomly selected test images demonstrate that PBTL-RDHEI is able to achieve an average embedding rate as large as 1.752 bpp and 2.003 bpp when block size is set to 2_2 and 3 _ 3, respectively.
In this paper, we first proposed a parametric binary tree labeling scheme (PBTL). Using PBTL, we then proposed a data embedding method (PBTL-DE) and further applied it into the encrypted images application (PBTL-RDHEI). The PBTL-DE is specific designed for encrypted-domain based application, because it significantly changed the pixel values in the image. PBTL-RDHEI is a full reversible method that both the secret data and original image can be extracted without any error. Experiment results and comparisons have shown that the PBTL-RDHEI significantly improved the embedding rate. Security analysis has demonstrated the robustness of PBTLRDHEI in withstanding brute-force and know/chosen-plaintext attacks.
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