1,317 research outputs found

    Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes

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    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

    Reversible Data Hiding in Encrypted Images Using MSBs Integration and Histogram Modification

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    This paper presents a reversible data hiding in encrypted image that employs based notions of the RDH in plain-image schemes including histogram modification and prediction-error computation. In the proposed method, original image may be encrypted by desire encryption algorithm. Most significant bit (MSB) of encrypted pixels are integrated to vacate room for embedding data bits. Integrated ones will be more resistant against failure of reconstruction if they are modified for embedding data bits. At the recipient, we employ chess-board predictor for lossless reconstruction of the original image by the aim of prediction-error analysis. Comparing to existent RDHEI algorithms, not only we propose a separable method to extract data bits, but also content-owner may attain a perfect reconstruction of the original image without having data hider key. Experimental results confirm that the proposed algorithm outperforms state of the art ones

    A Brief Review of RIDH

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    The Reversible image data hiding (RIDH) is one of the novel approaches in the security field. In the highly sensitive domains like Medical, Military, Research labs, it is important to recover the cover image successfully, Hence, without applying the normal steganography, we can use RIDH to get the better result. Reversible data hiding has a advantage over image data hiding that it can give you double security surely

    A Survey on Reversible Image Data Hiding Using the Hierarchical Block Embedding Technique

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    The use of graphics for data concealment has significantly advanced the fields of secure communication and identity verification. Reversible data hiding (RDH) involves hiding data within host media, such as images, while allowing for the recovery of the original cover. Various RDH approaches have been developed, including difference expansion, interpolation techniques, prediction, and histogram modification. However, these methods were primarily applied to plain photos. This study introduces a novel reversible image transformation technique called Block Hierarchical Substitution (BHS). BHS enhances the quality of encrypted images and enables lossless restoration of the secret image with a low Peak Signal-to-Noise Ratio (PSNR). The cover image is divided into non-overlapping blocks, and the pixel values within each block are encrypted using the modulo function. This ensures that the linear prediction difference in the block remains consistent before and after encryption, enabling independent data extraction without picture decryption. In order to address the challenges associated with secure multimedia data processing, such as data encryption during transmission and storage, this survey investigates the specific issues related to reversible data hiding in encrypted images (RDHEI). Our proposed solution aims to enhance security (low Mean Squared Error) and improve the PSNR value by applying the method to encrypted images

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

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    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
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