Watermarking Security Incorporating Natural Scene Statistics

Authors:
Jiangqun Ni;Rongyue Zhang;Chen Fang;Jiwu Huang;Chuntao Wang;Hyoung-Joong Kim
Affiliations:
School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, P. R. China 510275 and Guangdong Key Laboratory of Information Security Technology, Guangzhou, P.R. China 510275;Graduate School of Information Security, Korea University, Seoul, Korea 136-701;School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, P. R. China 510275;School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, P. R. China 510275 and Guangdong Key Laboratory of Information Security Technology, Guangzhou, P.R. China 510275;School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, P. R. China 510275;Graduate School of Information Security, Korea University, Seoul, Korea 136-701
Venue:
Information Hiding
Year:
2008

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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.