A Reversible Steganography Method With Statistical Features Maintained Based on the Difference Value

Tengfei Li,Huifeng Li,Hongtu Li,Liang Hu

doi:10.1109/access.2020.2964830

Tengfei Li, Huifeng Li + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.2964830

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Abstract

Reversible data hiding (RDH) is a technique that slightly alters digital media (e.g. images or videos) to embed secret messages while the original digital media can be completely recovered without any error after the hidden messages have been extracted. In the past more than one decade, hundreds of RDH algorithms have been reported, and among these algorithms, the difference histogram shifting (DHS) based methods have attracted much attention. With DHS-based RDH, high capacity and low distortion can be achieved efficiently. But there occurs one problem that, with DHS, the difference values to embed secret bits are explored, and the other difference values are shifted to create vacant spaces, it will cause the difference value histogram changing significantly and draw the attention of steganalyzers. So, this paper proposed a new idea for RDH based on the difference value and with statistical features maintained (SFM) with simple implementation and high scalability, we embed the secret messages by keeping the difference values that need to be modified in the original range, and the other difference values would not be shifted. In addition, we need the original difference values as the key to extract the secret messages. In order to expand the embedding capacity further, we designed two algorithms that embed message in two different difference values and four different difference values, and these two methods are named SFM_A and SFM_B respectively. SFM_B can support greater amount of embedded message than SFM_A, but brings greater changes to the original image, which could lead to the decline of PSNR and SSIM. The experimental results show that through our method, the histogram of difference values is well maintained, and the degree of distortion of the image is improved at the same time.

Highlights

Reversible data hiding (RDH) can imperceptibly hide data into digital images, and more importantly, the original image can be reconstructed completely after the embedded data have been extracted out [3]
The scheme compresses and distributes the information of the embedded secret image into all available bits in the cover image, which solves the obvious visual cues problem, and increases the embedding capacity. These papers used their own methods to solve the difficulties of using steganography due to image encryption, such as estimating some pixels before encryption, so that additional data could be embedded in the estimating errors, combining the compression and encryption of the image, compressing a series of selected bits taken from the encrypted image to make room for secret messages, and so on, these methods have made great strides in how to successfully apply RDH to the encrypting images, but how to improve the performance of RDH itself and apply it to the encryption domain are still problems we need to study
The main idea of our method is keeping the difference values that need to be modified in the original range, for example, if we choose the pixel blocks with difference pair {−1, 0} to embed secret messages, after the embedding process, the difference values of these blocks are still in {−1, 0}, and that is an example of embedding a piece of secret message in two difference values

Summary

INTRODUCTION

Reversible data hiding (RDH) can imperceptibly hide data into digital images, and more importantly, the original image can be reconstructed completely after the embedded data have been extracted out [3]. The scheme compresses and distributes the information of the embedded secret image into all available bits in the cover image, which solves the obvious visual cues problem, and increases the embedding capacity These papers used their own methods to solve the difficulties of using steganography due to image encryption, such as estimating some pixels before encryption, so that additional data could be embedded in the estimating errors, combining the compression and encryption of the image, compressing a series of selected bits taken from the encrypted image to make room for secret messages, and so on, these methods have made great strides in how to successfully apply RDH to the encrypting images, but how to improve the performance of RDH itself and apply it to the encryption domain are still problems we need to study.

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GENERAL PROCESS

ANALYSIS AND EXPERIMENT

CONCLUSION