JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model

Guorong Xuan; Xia Cui; Yun Q. Shi; Wen Chen; Xuefeng Tong; Cong Huang

doi:10.1109/icme.2007.4284797

JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model

Guorong Xuan, Xia Cui, Yun Q. Shi, Wen Chen, Xuefeng Tong, Cong Huang

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

This paper presents a new steganalysis scheme to attack JPEG steganography. The 360 dimensional feature vectors sensitive to data embedding process are derived from multidirectional Markov models in the JPEG coefficients domain. The class-wise non-principal components analysis (CNPCA) is proposed to classify steganograpghy in the high-dimensional feature vector space. The experimental results have demonstrated that the proposed scheme outperforms die existing steganalysis techniques in attacking modern JPEG steganographic schemes - F5, Outguess, MB1 and MB2.

Original language	English (US)
Title of host publication	Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
Publisher	IEEE Computer Society
Pages	903-906
Number of pages	4
ISBN (Print)	1424410177, 9781424410170
DOIs	https://doi.org/10.1109/icme.2007.4284797
State	Published - 2007
Event	IEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, China Duration: Jul 2 2007 → Jul 5 2007

Publication series

Name	Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

Other

Other	IEEE International Conference onMultimedia and Expo, ICME 2007
Country/Territory	China
City	Beijing
Period	7/2/07 → 7/5/07

All Science Journal Classification (ASJC) codes

Computer Graphics and Computer-Aided Design
Software

Access to Document

10.1109/icme.2007.4284797

Cite this

Xuan, G., Cui, X., Shi, Y. Q., Chen, W., Tong, X., & Huang, C. (2007). JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model. In Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007 (pp. 903-906). Article 4284797 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007). IEEE Computer Society. https://doi.org/10.1109/icme.2007.4284797

Xuan, Guorong ; Cui, Xia ; Shi, Yun Q. et al. / JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society, 2007. pp. 903-906 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007).

@inproceedings{d5ab80f85bd6487f9dadb6b05a880aa4,

title = "JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model",

abstract = "This paper presents a new steganalysis scheme to attack JPEG steganography. The 360 dimensional feature vectors sensitive to data embedding process are derived from multidirectional Markov models in the JPEG coefficients domain. The class-wise non-principal components analysis (CNPCA) is proposed to classify steganograpghy in the high-dimensional feature vector space. The experimental results have demonstrated that the proposed scheme outperforms die existing steganalysis techniques in attacking modern JPEG steganographic schemes - F5, Outguess, MB1 and MB2.",

author = "Guorong Xuan and Xia Cui and Shi, {Yun Q.} and Wen Chen and Xuefeng Tong and Cong Huang",

year = "2007",

doi = "10.1109/icme.2007.4284797",

language = "English (US)",

isbn = "1424410177",

series = "Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007",

publisher = "IEEE Computer Society",

pages = "903--906",

booktitle = "Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007",

address = "United States",

note = "IEEE International Conference onMultimedia and Expo, ICME 2007 ; Conference date: 02-07-2007 Through 05-07-2007",

}

Xuan, G, Cui, X, Shi, YQ, Chen, W, Tong, X & Huang, C 2007, JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model. in Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007., 4284797, Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007, IEEE Computer Society, pp. 903-906, IEEE International Conference onMultimedia and Expo, ICME 2007, Beijing, China, 7/2/07. https://doi.org/10.1109/icme.2007.4284797

JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model. / Xuan, Guorong; Cui, Xia; Shi, Yun Q. et al.
Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society, 2007. p. 903-906 4284797 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model

AU - Xuan, Guorong

AU - Cui, Xia

AU - Shi, Yun Q.

AU - Chen, Wen

AU - Tong, Xuefeng

AU - Huang, Cong

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N2 - This paper presents a new steganalysis scheme to attack JPEG steganography. The 360 dimensional feature vectors sensitive to data embedding process are derived from multidirectional Markov models in the JPEG coefficients domain. The class-wise non-principal components analysis (CNPCA) is proposed to classify steganograpghy in the high-dimensional feature vector space. The experimental results have demonstrated that the proposed scheme outperforms die existing steganalysis techniques in attacking modern JPEG steganographic schemes - F5, Outguess, MB1 and MB2.

AB - This paper presents a new steganalysis scheme to attack JPEG steganography. The 360 dimensional feature vectors sensitive to data embedding process are derived from multidirectional Markov models in the JPEG coefficients domain. The class-wise non-principal components analysis (CNPCA) is proposed to classify steganograpghy in the high-dimensional feature vector space. The experimental results have demonstrated that the proposed scheme outperforms die existing steganalysis techniques in attacking modern JPEG steganographic schemes - F5, Outguess, MB1 and MB2.

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M3 - Conference contribution

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T3 - Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

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Xuan G, Cui X, Shi YQ, Chen W, Tong X, Huang C. JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model. In Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society. 2007. p. 903-906. 4284797. (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007). doi: 10.1109/icme.2007.4284797

JPEG steganalysis based on classwise non-principal components analysis and multi-directional Markov model

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