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Blind steganalysis based on classifying feature vectors derived from images is becoming increasingly more powerful. For steganalysis of JPEG images, features derived directly in the embedding domain from DCT coefficients appear to achieve the best performance (e.g., the DCT features 10 and Markov features 21). The goal of this paper is to construct a new(More)
This paper summarizes the rst international challenge on steganalysis called BOSS (an acronym for Break Our Steganographic System). We explain the motivations behind the organization of the contest, its rules together with reasons for them, and the steganographic algorithm developed for the contest. Since the image databases created for the contest(More)
This paper presents a novel method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is LSB matching. First, arguments are provided for modeling differences between adjacent pixels using first-order and second-order Markov chains. Subsets of sample transition(More)
—This paper presents a method for detection of double JPEG compression and a maximum likelihood estimator of the primary quality factor. These methods are essential for construction of accurate targeted and blind steganalysis methods for JPEG images. The proposed methods use support vector machine classifiers with feature vectors formed by histograms of(More)
The goal of this paper is to determine the steganographic capacity of JPEG images (the largest payload that can be undetectably embedded) with respect to current best steganalytic methods. Additionally, by testing selected steganographic algorithms we evaluate the influence of specific design elements and principles, such as the choice of the JPEG(More)
YASS is a steganographic algorithm for digital images that hides messages robustly in a key-dependent transform domain so that the stego image can be subsequently compressed and distributed as JPEG. Given the fact that state-of-the-art blind steganalysis methods of 2007, when YASS was proposed, were unable to reliably detect YASS, in this paper we(More)
—A quantitative steganalyzer is an estima-tor of the number of embedding changes introduced by a specific embedding operation. Since for most algorithms the number of embedding changes correlates with the message length, quantitative steganalyzers are important forensic tools. In this paper, a general method for constructing quantitative steganalyzers from(More)
There are a number of recent information theoretic results demonstrating (under certain conditions) a sublinear relationship between the number of cover objects and their total steganographic capacity. In this paper we explain how these results may be adapted to the steganographic capacity of a single cover object, which under the right conditions should be(More)
—The aim of this paper is to construct a practical forensic steganalysis tool for JPEG images that can properly analyze both single-and double-compressed stego images and classify them to selected current steganographic methods. Although some of the individual modules of the steganalyzer were previously published by the authors, they were never tested as a(More)