JPEG image steganalysis utilizing both intrablock and interblock correlations
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ
DOI: 10.1109/ISCAS.2008.4542096 Conference: Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on
JPEG image steganalysis has attracted increasing attention recently. In this paper, we present an effective Markov process (MP) based JPEG steganalysis scheme, which utilizes both the intrablock and interblock correlations among JPEG coefficients. We compute transition probability matrix for each difference JPEG 2-D array to utilize the intrablock correlation, and "averaged" transition probability matrices for those difference mode 2-D arrays to utilize the interblock correlation. All the elements of these matrices are used as features for steganalysis. Experimental works over an image database of 7,560 JPEG images have demonstrated that this new approach has greatly improved JPEG steganalysis capability and outperforms the prior arts.
Available from: Hareesh Ravi
- "— The proposed method is compared with state-of-the-art filtering detection algorithms ([Conotter et al. 2013a] and [Zhang et al. 2014]) and is shown to perform better in most cases. Also, it is compared with popular feature extraction algorithms such as [Kirchner and Fridrich 2010], [Chen and Shi 2008], [Pevny and Fridrich 2007], [Kodovsky et al. 2012], [Cozzolino et al. 2014] and [Verdoliva et al. 2014] to show that the proposed technique gives better performance in filtering detection. — Proposed technique's counter anti-forensic effectiveness is shown by testing it against state-of-the-art compression [Fan et al. 2013] and median filter [Fan et al. 2015] antiforensic methods. "
- "The results demonstrated in Table 2, have been obtained by averaging over 20 random experiments. Table 2verifies that the proposed method has the lowest median testing error in comparison with the recently introduced schemes including91011121316], in the low embedding rates. Note that CF* (7850)scheme has shown the lowest median error, among the different presented embedding algorithms. "
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ABSTRACT: In this study, a blind steganalysis approach which accurately discloses low rate data hiding schemes is proposed. The absolute values of neighbouring joint density (absNJ) are used for feature extraction. In this way, the intra- and inter-block situations are employed providing a variety of different features. Aside from the absolute values of discrete cosine transform (DCT) coefficients, the differential DCT coefficients are also exploited to extract the features. Moreover, the absNJ features will be extended and used over differential DCT coefficients. It is shown that applying the Pth power of the DCT coefficients instead of their first power gains more discriminative features. Then, using the ensemble classifier, the cover image is discriminated from the stego one. Experimental results indicate the efficiency of the new scheme in comparison with the previously presented schemes.
Available from: sersc.org
- "By setting the threshold to construct 324 dimensional feature vectors, which can be more effective for classification. Subsequently, by introducing inter-block correlation of DCT coefficients, Chen et al.,  improved the method of Shi et al., . In Chen's scheme, they calculated block coefficient difference matrix of the Markov transition probability matrix, and finally constructed 486 dimensional feature vectors. "
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ABSTRACT: A blind steganalysis based on regional correlation and second-order Markov transition probability matrix is proposed for JPEG images. By analyzing the region correlation of JPEG image, the Markov transition probability matrix is used to capture the correlation of intra-block and inter-block DCT coefficients. In addition, the calibrated features are extracted from the calibrated images. The difference features between the original and calibrated images are used for training and classifying. Three different image libraries are used to detect the five kinds of typical JPEG steganography schemes. Experimental results show that, in comparison to the several effective steganalysis, the proposed scheme improves the detection accuracy on some JPEG-based steganography schemes, including outguess, Steghide and MB1.
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