The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Steganalysis by subtractive pixel adjacency matrix
Abstract
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 high-dimensional, we address the issue of curse of dimensionality using a feature selection algorithm and show that the curse did not occur in our experiments.
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Cites
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Guyon, I., Gunn, S. R., Nikravesh, M., & zadeh, L. N. (2006) · Cited by 1,658
Low-complexity image denoising based on statistical modeling of wavelet coefficients
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Statistics of natural images and models
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Fridrich, J. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-30114-1_6 · Cited by 459
Self-citationDetecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines
Lyu, S., & Farid, H. (2003) · Lecture Notes in Computer Science · doi:10.1007/3-540-36415-3_22 · Cited by 450
Steganalysis of additive-noise modelable information hiding:
Harmsen, J. J., & Pearlman, W. A. (2003) · SPIE Proceedings · doi:10.1117/12.476813 · Cited by 400
Cited by
Rich Models for Steganalysis of Digital Images
Fridrich, J., & Kodovsky, J. (2012) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2012.2190402 · Cited by 2,144
Self-citation”Break Our Steganographic System”: The Ins and Outs of Organizing BOSS
Bas, P., Filler, T., & Pevný, T. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-24178-9_5 · Cited by 1,250
Self-citationUniversal distortion function for steganography in an arbitrary domain
Holub, V., Fridrich, J., & Denemark, T. (2014) · EURASIP Journal on Information Security · doi:10.1186/1687-417x-2014-1 · Cited by 1,202
Self-citationA Deep Learning Approach to Universal Image Manipulation Detection Using a New Convolutional Layer
Bayar, B., & Stamm, M. C. (2016) · Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security · doi:10.1145/2909827.2930786 · Cited by 838
Content-Adaptive Steganography by Minimizing Statistical Detectability
Sedighi, V., Cogranne, R., & Fridrich, J. (2016) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2486744 · Cited by 573
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Metadata
- Authors
- Pevný, T., Bas, P., & Fridrich, J.
- Venue
- Proceedings of the 11th ACM workshop on Multimedia and security
- Publisher
- ACM
- Published
- 2009-09-07
- Pages
- 75-84
- OpenAlex
- W2031466562
- Cited by
- 769
- References
- 25
- FWCI
- 22.63
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Pevný, T., Bas, P., & Fridrich, J. (2009). Steganalysis by subtractive pixel adjacency matrix. Proceedings of the 11th ACM workshop on Multimedia and security. https://doi.org/10.1145/1597817.1597831
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