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37
Designing steganographic distortion using directional filters
 In Fourth IEEE International Workshop on Information Forensics and Security
, 2012
"... This paper presents a new approach to defining additive steganographic distortion in the spatial domain. The change in the output of directional highpass filters after changing one pixel is weighted and then aggregated using the reciprocal Hölder norm to define the individual pixel costs. In contra ..."
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Cited by 20 (15 self)
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This paper presents a new approach to defining additive steganographic distortion in the spatial domain. The change in the output of directional highpass filters after changing one pixel is weighted and then aggregated using the reciprocal Hölder norm to define the individual pixel costs. In contrast to other adaptive embedding schemes, the aggregation rule is designed to force the embedding changes to highly textured or noisy regions and to avoid clean edges. Consequently, the new embedding scheme appears markedly more resistant to steganalysis using rich models. The actual embedding algorithm is realized using syndrometrellis codes to minimize the expected distortion for a given payload. 1.
Steganalysis of JPEG Images Using Rich Models
"... In this paper, we propose a rich model of DCT coefficients in a JPEG file for the purpose of detecting steganographic embedding changes. The model is built systematically as a union of smaller submodels formed as joint distributions of DCT coefficients from their frequency and spatial neighborhoods ..."
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In this paper, we propose a rich model of DCT coefficients in a JPEG file for the purpose of detecting steganographic embedding changes. The model is built systematically as a union of smaller submodels formed as joint distributions of DCT coefficients from their frequency and spatial neighborhoods covering a wide range of statistical dependencies. Due to its high dimensionality, we combine the rich model with ensemble classifiers and construct detectors for six modern JPEG domain steganographic schemes: nsF5, modelbased steganography, YASS, and schemes that use side information at the embedder in the form of the uncompressed image: MME, BCH, and BCHopt. The resulting performance is contrasted with previously proposed feature sets of both low and high dimensionality. We also investigate the performance of individual submodels when grouped by their type as well as the effect of Cartesian calibration. The proposed rich model delivers superior performance across all tested algorithms and payloads. 1.
Design of Adaptive Steganographic Schemes for Digital Images
 Proceedings of SPIE, Electronic Imaging, Media Watermarking, Security, and Forensics XIII
, 2011
"... Most steganographic schemes for real digital media embed messages by minimizing a suitably dened distortion function. In practice, this is often realized by syndrome codes which oer nearoptimal ratedistortion performance. However, the distortion functions are designed heuristically and the resulti ..."
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Cited by 20 (9 self)
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Most steganographic schemes for real digital media embed messages by minimizing a suitably dened distortion function. In practice, this is often realized by syndrome codes which oer nearoptimal ratedistortion performance. However, the distortion functions are designed heuristically and the resulting steganographic algorithms are thus suboptimal. In this paper, we present a practical framework for optimizing the parameters of additive distortion functions to minimize statistical detectability. We apply the framework to digital images in both spatial and DCT domain by rst dening a rich parametric model which assigns a cost of making a change at every cover element based on its neighborhood. Then, we present a practical method for optimizing the parameters with respect to a chosen detection metric and feature space. We show that the size of the margin between support vectors in softmargin SVMs leads to a fast detection metric and that methods minimizing the margin tend to be more secure w.r.t. blind steganalysis. The parameters obtained by the NelderMead simplexreection algorithm for spatial and DCTdomain images are presented and the new embedding methods are tested by blind steganalyzers utilizing various feature sets. Experimental results show that as few as 80 images are sucient for obtaining good candidates for parameters of the cost model, which allows us to speed up the parameter search.
MULTIVARIATE GAUSSIAN MODEL FOR DESIGNING ADDITIVE DISTORTION FOR STEGANOGRAPHY
"... Currently, the most successful approach to steganography in empirical objects, such as digital media, is to cast the embedding problem as source coding with a fidelity constraint. The sender specifies the costs of changing each cover element and then embeds a given payload by minimizing the total em ..."
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Cited by 8 (5 self)
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Currently, the most successful approach to steganography in empirical objects, such as digital media, is to cast the embedding problem as source coding with a fidelity constraint. The sender specifies the costs of changing each cover element and then embeds a given payload by minimizing the total embedding cost. Since efficient practical codes exist that embed near the rate–distortion bound, the remaining task left to the steganographer is the fidelity measure – the choice of the costs. In the past, the costs were obtained either in an ad hoc manner or determined from the effects of embedding in a chosen feature space. In this paper, we adopt a different strategy in which the cover is modeled as a sequence of independent but not necessarily identically distributed quantized Gaussians and the embedding change probabilities are derived to minimize the total KL divergence within the chosen model for a given embedding operation and payload. Despite the simplicity of the adopted model, the resulting stegosystem exhibits security that is comparable to current stateoftheart methods methods across a wide range of payloads. Index Terms — Steganography, multivariate Gaussian cover, additive distortion function, syndrometrellis codes, steganalysis 1.
Moving Steganography and Steganalysis from the Laboratory into the Real World
"... There has been an explosion of academic literature on steganography and steganalysis in the past two decades. With a few exceptions, such papers address abstractions of the hiding and detection problems, which arguably have become disconnected from the real world. Most published results, including b ..."
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Cited by 8 (5 self)
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There has been an explosion of academic literature on steganography and steganalysis in the past two decades. With a few exceptions, such papers address abstractions of the hiding and detection problems, which arguably have become disconnected from the real world. Most published results, including by the authors of this paper, apply “in laboratory conditions ” and some are heavily hedged by assumptions and caveats; significant challenges remain unsolved in order to implement good steganography and steganalysis in practice. This position paper sets out some of the important questions which have been left unanswered, as well as highlighting some that have already been addressed successfully, for steganography and steganalysis to be used in the real world.
Universal Distortion Function for Steganography in an Arbitrary Domain
, 2013
"... Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the steganographer since efficient practical codes ..."
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Cited by 6 (5 self)
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Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the steganographer since efficient practical codes exist that embed near the payload–distortion bound. The practitioner’s goal is to design the distortion to obtain a scheme with a high empirical statistical detectability. In this paper, we propose a universal distortion design called UNIWARD (UNIversal WAvelet Relative Distortion) that can be applied for embedding in an arbitrary domain. The embedding distortion is computed as a sum of relative changes of coefficients in a directional filter bank decomposition of the cover image. The directionality forces the embedding changes to such parts of the cover object that are difficult to model in multiple directions, such as textures or noisy regions, while avoiding smooth regions or clean edges. We demonstrate experimentally using rich models as well as targeted attacks that steganographic methods built using UNIWARD match or outperform the current state of the art in the spatial domain, JPEG domain, and sideinformed JPEG domain. 1
Minimizing additive distortion functions with nonbinary embedding operation in steganography
 In Information Forensics and Security (WIFS), 2010 IEEE International Workshop on
, 2010
"... Most practical steganographic algorithms for empirical covers embed messages by minimizing a sum of perpixel distortions. Current nearoptimal codes for this minimization problem [7] are limited to a binary embedding operation. In this paper, we extend this work to embedding operations of larger ca ..."
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Cited by 5 (0 self)
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Most practical steganographic algorithms for empirical covers embed messages by minimizing a sum of perpixel distortions. Current nearoptimal codes for this minimization problem [7] are limited to a binary embedding operation. In this paper, we extend this work to embedding operations of larger cardinality. The need for embedding changes of larger amplitude and the merit of this construction are confirmed experimentally by implementing an adaptive embedding algorithm for digital images and comparing its security to other schemes. 1.
Steganography using gibbs random fields
 Proceedings of the 12th ACM Multimedia & Security Workshop, MM&#38;Sec ’10
, 2010
"... Many steganographic algorithms for empirical covers are designed to minimize embedding distortion. In this work, we provide a general framework and practical methods for embedding with an arbitrary distortion function that does not have to be additive over pixels and thus can consider interactions a ..."
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Cited by 3 (1 self)
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Many steganographic algorithms for empirical covers are designed to minimize embedding distortion. In this work, we provide a general framework and practical methods for embedding with an arbitrary distortion function that does not have to be additive over pixels and thus can consider interactions among embedding changes. The framework evolves naturally from a parallel made between steganography and statistical physics. The Gibbs sampler is the key tool for simulating the impact of optimal embedding and for constructing practical embedding algorithms. The proposed framework reduces the design of secure steganography in empirical covers to the problem of finding suitable local potentials for the distortion function that correlate with statistical detectability in practice. We work out the proposed methodology in detail for a specific choice of the distortion function and validate the approach through experiments.
Contentadaptive pentary steganography using the multivariate generalized gaussian cover model
 IS&T/SPIE Electronic Imaging conf
"... The vast majority of steganographic schemes for digital images stored in the raster format limit the amplitude of embedding changes to the smallest possible value. In this paper, we investigate the possibility to further improve the empirical security by allowing the embedding changes in highly text ..."
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Cited by 3 (3 self)
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The vast majority of steganographic schemes for digital images stored in the raster format limit the amplitude of embedding changes to the smallest possible value. In this paper, we investigate the possibility to further improve the empirical security by allowing the embedding changes in highly textured areas to have a larger amplitude and thus embedding there a larger payload. Our approach is entirely model driven in the sense that the probabilities with which the cover pixels should be changed by a certain amount are derived from the cover model to minimize the power of an optimal statistical test. The embedding consists of two steps. First, the sender estimates the cover model parameters, the pixel variances, when modeling the pixels as a sequence of independent but not identically distributed generalized Gaussian random variables. Then, the embedding change probabilities for changing each pixel by 1 or 2, which can be transformed to costs for practical embedding using syndrometrellis codes, are computed by solving a pair of nonlinear algebraic equations. Using rich models and selectionchannelaware features, we compare the security of our scheme based on the generalized Gaussian model with pentary versions of two popular embedding algorithms: HILL and SUNIWARD. 1.
Further Study on the Security of SUNIWARD
"... Recently, a new steganographic method was introduced that utilizes a universal distortion function called UNIWARD. The distortion between the cover and stego image is computed as a sum of relative changes of wavelet coefficients representing both images. As already pointed out in the original publi ..."
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Cited by 2 (2 self)
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Recently, a new steganographic method was introduced that utilizes a universal distortion function called UNIWARD. The distortion between the cover and stego image is computed as a sum of relative changes of wavelet coefficients representing both images. As already pointed out in the original publication, the selection channel of the spatial version of UNIWARD (the version that hides messages in pixel values called SUNIWARD) exhibits unusual properties – in highly textured and noisy regions the embedding probabilities form interleaved streaks of low and high embedding probability. While the authors of UNIWARD themselves hypothesized that such an artifact in the embedding probabilities may jeopardize its security, experiments with stateoftheart rich models did not reveal any weaknesses. Using the fact that the cover embedding probabilities can be approximately estimated from the stego image, we introduce the novel concept of contentselective residuals and successfully attack SUNIWARD. We also show that this attack, which is made possible by a faulty probabilistic selection channel, can be prevented by properly adjusting the stabilizing constant in the UNIWARD distortion function.