A Framework to Reversible Data Hiding Using Histogram-Modification

A Novel method of Stegnography to achieve Reversible Data Hiding (RDH) is proposed using Histogram Modification (HM). In this paper the HM technique is revisited and a general framework to construct HM-based RDH is presented by simply designing the shifting and embedding functions on the cover image. The Secret Image is embedded inside the cover image using several steps of specific shifting of pixels with an order. The secret image or logo is retrieved without any loss in data on the cover and as well as in the secrete image. The Experimental results show the better Peak Signal to Noise Ratio (PSNR) with the existing methods

Reversible data hiding in JPEG images based on adjustable padding

In this paper, we propose a reversible data hiding scheme that enables an adjustable amount of information to be embedded in JPEG images based on padding strategy. The proposed embedding algorithm only modifies, in a subtle manner, an adjustable number of zero-valued quantised DCT coefficients to embed the message. Hence, compared with a state-of-the-art based on histogram shifting, the proposed scheme has a relatively low distortion to the host images. In addition to this, we found that by representing the message in ternary instead of in binary, we can embed a greater amount of information while the level of distortion remains unchanged. Experimental results support that the proposed scheme can achieve better visual quality of the marked JPEG image than the histogram shifting based scheme. The proposed scheme also outperforms this state-of-the-art in terms of the ease of implementation

Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on the local complexity of a pixel is used to collect the PPEs to generate an ordered PPE sequence so that, smaller PPEs will be processed first for data embedding. By reversibly shifting the PPE histogram (PPEH) with optimized parameters, the pixels corresponding to the altered PPEH bins can be finally modified to carry the secret data. Experimental results have implied that the proposed method can benefit from the prediction procedure of the PEs, sorting technique as well as parameters selection, and therefore outperform some state-of-the-art works in terms of payload-distortion performance when applied to different images.Comment: There has no technical difference to previous versions, but rather some minor word corrections. A 2-page summary of this paper was accepted by ACM IH&MMSec'16 "Ongoing work session". My homepage: hzwu.github.i

General Framework of Reversible Watermarking Based on Asymmetric Histogram Shifting of Prediction Error

This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. Different from the conventional algorithms using single-prediction scheme to create symmetric histogram, the proposed method employs a multi-prediction scheme, which calculates multiple prediction values for the pixels. Then, the suitable value would be selected by two dual asymmetric selection functions to construct two asymmetric error histograms. Finally, the watermark is embedded in the two error histograms separately utilizing a complementary embedding strategy. The proposed framework provides a new perspective for the research of reversible watermarking, which brings about many benefits for the information security

Multilayer Reversible Data Hiding Via Histogram Shifting

Concealing messages from unauthorised people has been desired since written communication first began. With advancements in digital communication technology and the growth of computer power and storage, the difficulty of ensuring the privacy of individuals and the protection of copyright has become increasingly challenging. Steganography finds a role in attempting to address these growing concerns. Problems arise in the steganography method because of the trade-off between capacity and imperceptibility whereby increasing the embedding capacity increases the distortion in the stego object and it thus becomes suspect. Another problem is concerned with non-retrieval of the original cover object whereby misplacing data could be crucial for example in the case of medical images. Reversible data hiding technique based on histogram shifting addresses the problem of retrieving the original cover. Embedding the secret message by shifting the histogram between the pair of the peak and minimum points wastes the embedding capacity and does not control the distortion in the stego image for various secret messages sizes. In this research, a technique for reversible data hiding is proposed which enables the retrieval of both the hidden secret message and the original image at the receiver’s side. The proposed technique considers the size of the secret message and the distribution of the colour values within the cover image to determine the value of the optimal pair or set of container and carried colours within the best sub image instead of the pair of peak and minimum points. The experimental results show that the proposed technique increases the embedding capacity within the cover image and produces a stego image with a high peak signal-to-noise ratio value. In addition, the experimental results show that by using the proposed re-shifting and extraction formulas, the technique has the ability to extract the hidden data and retrieve the original images from the stego images. In comparison to the traditional histogram-shifting techniques, the proposed technique significantly improves the stego image quality and the embedding capacity. Thus, this research has contributed to two principles, namely improvements in capacity and quality