95 research outputs found

    Analysis of MHPDM algorithm for data hiding in JPEG images

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    In the recent years, there has been a great deal of interest in developing a secure algorithm for hiding information in images, or steganography. There has also been a lot of research in steganalysis of images, which deals with the detection of hidden information in supposedly natural images. The first section of this thesis reviews the steganography algorithms and steganalysis techniques developed in the last few years. It discusses the breadth of steganographic algorithms and steganalytic techniques, starting with the earliest, based on LSB flipping of the DCT coefficients, to more recent and sophisticated algorithms for data hiding and equally clever steganalytic techniques. The next section focuses on the steganographic algorithm, MHPDM which was first developed by Eggers and then modified by Tzschoppe, Bauml, Huber and Kaup. The MHPDM algorithm preserves the histogram of the stego image and is thus perfectly secure in terms of Cachin\u27s security definition. The MHPDM algorithm is explained in detail and implemented in MATLAB. It is then tested on numerous images and steganalysed using Dr. Fridrich\u27s recent feature-based steganalytic technique. The thesis concludes with observations about the detectibility of MHPDM using feature-based steganalysis for different payloads (embedded message lengths)

    A Spatial Domain Image Steganography Technique Based on Plane Bit Substitution Method

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    Steganography is the art and science of hiding information by embedding data into cover media. In this paper we propose a new method of information hiding in digital image in spatial domain. In this method we use Plane Bit Substitution Method (PBSM) technique in which message bits are embedded into the pixel value(s) of an image. We first, proposed a Steganography transformation machine (STM) for solving Binary operation for manipulation of original image with help to least significant bit (LSB) operator based matching. Second, we use pixel encryption and decryption techniques under theoretical and experimental evolution. Our experimental, techniques are sufficient to discriminate analysis of stego and cover image as each pixel based PBSM, and operand with LSB

    Spread spectrum-based video watermarking algorithms for copyright protection

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    Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

    CNN Based Adversarial Embedding with Minimum Alteration for Image Steganography

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    Historically, steganographic schemes were designed in a way to preserve image statistics or steganalytic features. Since most of the state-of-the-art steganalytic methods employ a machine learning (ML) based classifier, it is reasonable to consider countering steganalysis by trying to fool the ML classifiers. However, simply applying perturbations on stego images as adversarial examples may lead to the failure of data extraction and introduce unexpected artefacts detectable by other classifiers. In this paper, we present a steganographic scheme with a novel operation called adversarial embedding, which achieves the goal of hiding a stego message while at the same time fooling a convolutional neural network (CNN) based steganalyzer. The proposed method works under the conventional framework of distortion minimization. Adversarial embedding is achieved by adjusting the costs of image element modifications according to the gradients backpropagated from the CNN classifier targeted by the attack. Therefore, modification direction has a higher probability to be the same as the sign of the gradient. In this way, the so called adversarial stego images are generated. Experiments demonstrate that the proposed steganographic scheme is secure against the targeted adversary-unaware steganalyzer. In addition, it deteriorates the performance of other adversary-aware steganalyzers opening the way to a new class of modern steganographic schemes capable to overcome powerful CNN-based steganalysis.Comment: Submitted to IEEE Transactions on Information Forensics and Securit

    An Adaptive Steganography Scheme Based on Visual Quality and Embedding Capacity Improvement

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    In this paper, a steganography technique using LSB substitution and PVD method is presented as an adaptive scheme in the spatial domain. Our method partitions the grayscale image into several non-overlapping blocks with three consecutive pixels. The embedding algorithm can both replace the secret data with the LSBs of the middle pixel and embed it in the difference values between the middle pixel and its two neighboring pixels of the cover-block. The number of secret bits is determined adaptively based on the range divisions for embedding in the difference value. We define a new range division on gray level which takes into account a larger embedding capacity for bits. After the embedding, the proposed method detects the pixels which are sensitive to hyper distortion. Then, the embedding process will be repeated to produce insignificant visual distortion in those pixels. Our experimental results demonstrate that this iterative steganography scheme prevents significant visual distortion into stego-image. The generated PSNR values are higher than the corresponding values of the most commonly used methods, discussed in this study. Furthermore, the experimental results show that the hiding capacity increased enormously when the proposed range division is used. Finally, we illustrate that the method can pass RS and steganalysis detector attacks.DOI:http://dx.doi.org/10.11591/ijece.v4i4.630
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