Steganalysis by subtractive pixel adjacency matrix

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Steganalysis by subtractive pixel adjacency matrix
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 probability matrices are then used as features for a steganalyzer implemented by support vector machines. The accuracy of the presented steganalyzer is evaluated on LSB matching and four different databases. The steganalyzer achieves superior accuracy with respect to prior art and provides stable results across various cover sources. Since the feature set based on second-order Markov chain is highdimensional, we address the issue of curse of dimensionality using a feature selection algorithm and show that the curse did not occur in our experiments. Categories and Subject Descriptors D.2.11 [Software Engineering]: Software Architectur...
Tomás Pevný, Patrick Bas, Jessica J.
Added 31 Jan 2011
Updated 31 Jan 2011
Type Journal
Year 2010
Where TIFS
Authors Tomás Pevný, Patrick Bas, Jessica J. Fridrich
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