The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Steganalysis of Adaptive JPEG Steganography Using 2D Gabor Filters
Abstract
Adaptive JPEG steganographic schemes are difficult to preserve the image texture features in all scales and orientations when the embedding changes are constrained to the complicated texture regions, then a steganalysis feature extraction method is proposed based on 2 dimensional (2D) Gabor filters. The 2D Gabor filters have certain optimal joint localization properties in the spatial domain and in the spatial frequency domain. They can describe the image texture features from different scales and orientations, therefore the changes of image statistical characteristics caused by steganography embedding can be captured more effectively. For the proposed feature extraction method, the decompressed JPEG image is filtered by 2D Gabor filters with different scales and orientations firstly. Then, the histogram features are extracted from all the filtered images.Lastly, the ensemble classifier is used to assemble the proposed steganalysis feature as well as the final steganalyzer. The experimental results show that the proposed steganalysis feature can achieve a competitive performance by comparing with the other steganalysis features when they are used for the detection performance of adaptive JPEG steganography such as UED, JUNIWARD and SI-UNIWARD.
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Cites
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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
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”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
Ensemble Classifiers for Steganalysis of Digital Media
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Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes
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Comparison of texture features based on Gabor filters
Grigorescu, S. E., Petkov, N., & Kruizinga, P. (2002) · IEEE Transactions on Image Processing · doi:10.1109/tip.2002.804262 · Cited by 742
Defending against statistical steganalysis
Provos, N. (2001) · Cited by 575
Multimedia Tools and Applications
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Low-Complexity Features for JPEG Steganalysis Using Undecimated DCT
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Cited by
CNN-Based Adversarial Embedding for Image Steganography
Tang, W., Li, B., Tan, S., Barni, M., & Huang, J. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2891237 · Cited by 292
JPEG steganalysis based on ResNeXt with Gauss partial derivative filters
Su, A., He, X., & Zhao, X. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09350-2 · Cited by 13
Metadata
- Authors
- Song, X., Liu, F., Yang, C., Luo, X., & Zhang, Y.
- Venue
- Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security
- Publisher
- ACM
- Published
- 2015-06-17
- Pages
- 15-23
- OpenAlex
- W2055625960
- Cited by
- 300
- References
- 19
- FWCI
- 10.53
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Song, X., Liu, F., Yang, C., Luo, X., & Zhang, Y. (2015). Steganalysis of Adaptive JPEG Steganography Using 2D Gabor Filters. Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security. https://doi.org/10.1145/2756601.2756608
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