Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes

Peer-reviewedIn this paper, several steganalytic techniques designed to detect the existence of hidden messages using histogram shifting schemes are presented. Firstly, three techniques to identify specific histogram shifting data hiding schemes, based on detectable visible alterations on the histogram or abnormal statistical distributions, are suggested. Afterwards, a general technique capable of detecting all the analyzed histogram shifting data hiding methods is suggested. This technique is based on the effect of histogram shifting methods on the ¿volatility¿ of the histogram of the difference image. The different behavior of volatility whenever new data are hidden makes it possible to identify stego and cover images

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

Adaptive Reversible Data Hiding Scheme for Digital Images Based on Histogram Shifting

Existing histogram based reversible data hiding schemes use only absolute difference values between the neighboring pixels of a cover image. In these schemes, maxima and minima points at maximum distance are selected in all the blocks of the image which causes shifting of the large number of pixels to embed the secret data. This shifting produces more degradation in the visual quality of the marked image. In this work, the cover image is segmented into blocks, which are classified further into complex and smooth blocks using a threshold value. This threshold value is optimized using firefly algorithm. Simple difference values between the neighboring pixels of complex blocks have been utilized to embed the secret data bits. The closest maxima and minima points in the histogram of the difference blocks are selected so that number of shifted pixels get reduced, which further reduces the distortion in the marked image. Experimental results prove that the proposed scheme has better performance as compared to the existing schemes. The scheme shows minimum distortion and large embedding capacity. Novelty of work is the usage of negative difference values of complex blocks for secret data embedding with the minimal number of pixel shifting

Reversible Data Hiding Using Hybrid Method of Difference Expansion on Medical Image

Data hiding in the image can cause permanent distortion (irreversible), in other applications such as medical images, distortion can cause misdiagnosis. To overcome these problems, a special scheme is required for the embedding data on medical image. Reversible data hiding is a scheme that can restore the image to original image without distortion after the embedded information is extracted. Difference Expansion (DE) is one of the schemes in reversible data hiding that is simple and easy to implement. In this paper, we propose two schemes based a hybrid combination of DE to increase on capacity and visual quality. Medical image has characteristics is the large of smooth block areas, in which DE method is applied to the non-smooth areas image. We used four different medical images to evaluate the proposed scheme. The results showed that the proposed scheme has a high capacity and better visual quality than the original scheme and similar schemes have been proposed previously. Embedding capacity of the proposed scheme is up to 0.66 bpp with visual quality of PSNR value is up to 48 dB

Difference-Expansion Based Reversible and Visible Image Watermarking Scheme

[[conferencetype]]國內[[conferencedate]]20150817~20150819[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]JiaoSi, Taiwa

Separable Reversible Data Hiding in Encrypted Images Based on Two-Dimensional Histogram Modification

An efficient method of completely separable reversible data hiding in encrypted images is proposed. The cover image is first partitioned into nonoverlapping blocks and specific encryption is applied to obtain the encrypted image. Then, image difference in the encrypted domain can be calculated based on the homomorphic property of the cryptosystem. The data hider, who does not know the original image content, may reversibly embed secret data into image difference based on two-dimensional difference histogram modification. Data extraction is completely separable from image decryption; that is, data extraction can be done either in the encrypted domain or in the decrypted domain, so that it can be applied to different application scenarios. In addition, data extraction and image recovery are free of any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme