Watermarking security incorporating natural scene statistics

Jiangqun Ni; Rongyue Zhang; Chen Fang; Jiwu Huang; Chuntao Wang; Hyoung Joong Kim

doi:10.1007/978-3-540-88961-8_10

Watermarking security incorporating natural scene statistics

Jiangqun Ni^*, Rongyue Zhang, Chen Fang, Jiwu Huang, Chuntao Wang, Hyoung Joong Kim

^*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Watermarking security has emerged as the domain of extensive research in recent years. This paper presents both information theoretic analysis and practical attack algorithm for spread-spectrum based watermarking security incorporating natural scene statistics (NSS) model. Firstly, the Gaussian scale mixture (GSM) is introduced as the NSS model. The security is quantified by the mutual information between the observed watermarked signals and the secret carriers. The new security measures are then derived based on the GSM model, which allows for more accurate evaluation of watermarking security. Finally, the practical attack algorithm is developed in the framework of variational Bayesian ICA, which is shown to increase the performance and flexibility by allowing incorporation of prior knowledge of host signal. Extensive simulations are carried out to demonstrate the feasibility and effectiveness of the proposed algorithm.

Original language	English
Title of host publication	Information Hiding - 10th International Workshop, IH 2008, Revised Selected Papers
Publisher	Springer Verlag
Pages	132-146
Number of pages	15
ISBN (Print)	3540889604, 9783540889601
DOIs	https://doi.org/10.1007/978-3-540-88961-8_10
Publication status	Published - 2008
Event	10th International Workshop on Information Hiding, IH 2008 - Santa Barbara, CA, United States Duration: 2008 May 19 → 2008 May 21

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5284 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	10th International Workshop on Information Hiding, IH 2008
Country/Territory	United States
City	Santa Barbara, CA
Period	08/5/19 → 08/5/21

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-88961-8_10

Cite this

Ni, J., Zhang, R., Fang, C., Huang, J., Wang, C., & Kim, H. J. (2008). Watermarking security incorporating natural scene statistics. In Information Hiding - 10th International Workshop, IH 2008, Revised Selected Papers (pp. 132-146). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5284 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-88961-8_10

Watermarking security incorporating natural scene statistics. / Ni, Jiangqun; Zhang, Rongyue; Fang, Chen et al.
Information Hiding - 10th International Workshop, IH 2008, Revised Selected Papers. Springer Verlag, 2008. p. 132-146 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5284 LNCS).

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

Ni, J, Zhang, R, Fang, C, Huang, J, Wang, C & Kim, HJ 2008, Watermarking security incorporating natural scene statistics. in Information Hiding - 10th International Workshop, IH 2008, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5284 LNCS, Springer Verlag, pp. 132-146, 10th International Workshop on Information Hiding, IH 2008, Santa Barbara, CA, United States, 08/5/19. https://doi.org/10.1007/978-3-540-88961-8_10

Ni J, Zhang R, Fang C, Huang J, Wang C, Kim HJ. Watermarking security incorporating natural scene statistics. In Information Hiding - 10th International Workshop, IH 2008, Revised Selected Papers. Springer Verlag. 2008. p. 132-146. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-88961-8_10

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abstract = "Watermarking security has emerged as the domain of extensive research in recent years. This paper presents both information theoretic analysis and practical attack algorithm for spread-spectrum based watermarking security incorporating natural scene statistics (NSS) model. Firstly, the Gaussian scale mixture (GSM) is introduced as the NSS model. The security is quantified by the mutual information between the observed watermarked signals and the secret carriers. The new security measures are then derived based on the GSM model, which allows for more accurate evaluation of watermarking security. Finally, the practical attack algorithm is developed in the framework of variational Bayesian ICA, which is shown to increase the performance and flexibility by allowing incorporation of prior knowledge of host signal. Extensive simulations are carried out to demonstrate the feasibility and effectiveness of the proposed algorithm.",

author = "Jiangqun Ni and Rongyue Zhang and Chen Fang and Jiwu Huang and Chuntao Wang and Kim, \{Hyoung Joong\}",

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AB - Watermarking security has emerged as the domain of extensive research in recent years. This paper presents both information theoretic analysis and practical attack algorithm for spread-spectrum based watermarking security incorporating natural scene statistics (NSS) model. Firstly, the Gaussian scale mixture (GSM) is introduced as the NSS model. The security is quantified by the mutual information between the observed watermarked signals and the secret carriers. The new security measures are then derived based on the GSM model, which allows for more accurate evaluation of watermarking security. Finally, the practical attack algorithm is developed in the framework of variational Bayesian ICA, which is shown to increase the performance and flexibility by allowing incorporation of prior knowledge of host signal. Extensive simulations are carried out to demonstrate the feasibility and effectiveness of the proposed algorithm.

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ER -

Watermarking security incorporating natural scene statistics

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