The Parallel-Gaussian Watermarking Game

Moulin, Pierre; Mihcak, M.K.

doi:10.1109/tit.2003.822578

Cited by 41 publications

(58 citation statements)

References 18 publications

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“…The problem of finding the capacity can be viewed as a game across the parallel gaussian channels [11,12] where both embedder and attacker attempt to maximize their advantage in every channel. For the capacity estimates to be meaningful distortion constraints are imposed upon both the embedder and the attacker.…”

Section: ) Watermarking Gamementioning

confidence: 99%

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Watermarking for Multimedia Security Using Complex Wavelets

Thompson¹,

Bouridane²,

Kurugöllü³

et al. 2010

JMM

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Abstract-This paper investigates the application of complex wavelet transforms to the field of digital data hiding. Complex wavelets offer improved directional selectivity and shift invariance over their discretely sampled counterparts allowing for better adaptation of watermark distortions to the host media. Two methods of deriving visual models for the watermarking system are adapted to the complex wavelet transforms and their performances are compared. To produce improved capacity a spread transform embedding algorithm is devised, this combines the robustness of spread spectrum methods with the high capacity of quantization based methods. Using established information theoretic methods, limits of watermark capacity are derived that demonstrate the superiority of complex wavelets over discretely sampled wavelets. Finally results for the algorithm against commonly used attacks demonstrate its robustness and the improved performance offered by complex wavelet transforms.Index Terms-Complex wavelets, spread transform, capacity, human visual system, watermarking.

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Section: ) Watermarking Gamementioning

confidence: 99%

“…To address this, Moulin et al [11,12] have developed an information theoretic model that models the watermarking situation as a game between the attacker and embedder with each trying to maximize their advantage over a range of Gaussian distributed channels.…”

Section: Introductionmentioning

confidence: 99%

Watermarking for Multimedia Security Using Complex Wavelets

Thompson¹,

Bouridane²,

Kurugöllü³

et al. 2010

JMM

View full text Add to dashboard Cite

show abstract

“…In order to make the stated game explicitly solvable, signals are modeled by parallel colored independent gaussian processes such it has been done in [6]. Host and forged signals are respectively modeled as x ∼ N (0, R1) and y |H 0 ∼ N (0, R0), where R1 and R0 are symmetrical and positive definite N × N correlation matrices.…”

Section: Parallel Gaussian Signals and Neyman-pearson Testmentioning

confidence: 99%

“…For stationary gaussian processes, the Karhunen-Loève Transform (KLT) is approximatively equal to the DCT whenever N is large [6]. Each component can be viewed as a frequency component.…”

Section: Parallel Gaussian Signals and Neyman-pearson Testmentioning

confidence: 99%

Spread-Spectrum Substitution watermarking Game

Boyer¹,

Duhamel²,

Blanc-Talon

2006

2006 IEEE International Conference on Multimedia and Expo

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In the integrity checking context of multimedia contents, a malicious user aims at devising a forged content in order to fool a watermarker by making him use as a genuine content. By considering that the watermark acts as an integrity stamp, the false-alarm probability to recover the watermark signature in a forged content is the criterion of interest. We study and solve a game for this criterion between a watermarker and a falsifier which is allowed to perform a substitution attack, i.e. replace the watermarked signal by a non-watermarked content. As for the watermarker, we are concerned with additive spread-spectrum (SS) embedding. Signals are modeled by parallel colored gaussian processes. Due to the intractability of the false-alarm probability, we resort to Chernoff bound as an alternative cost. Our study confirms some common heuristics: the best attacker choice is to substitute the watermarked host signal using a signal which has very close statistics to the original host signal. The best watermarker strategy is to embed the watermark into the weakest frequency power components of the host signal. We finally consider the consequences of these results in terms of frequency embedding domain for an image SS watermarking scheme which has to be robust to compression. This reveals notable differences with informed scalar quantized-based schemes.

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“…Although the two properties above are similar to those satisfied by the solution to the Gaussian data-hiding problem [4], the optimal power allocations are completely different. Fig.…”

Section: Solution Of Maxmin Problem (6)mentioning

confidence: 94%

Nonadditive Gaussian watermarking and its application to wavelet-based image watermarking

Moulin¹,

Ivanović²

Proceedings. International Conference on Image Processing

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This paper extends our recent game-theoretic approach [1] to design and embed watermarks in Gaussian signals in the presence of an adversary. The detector solves a binary hypothesis testing problem. The system is designed to minimize probability of error under the worst-case attack in a prescribed class of attacks. In this paper, the embedder is allowed to filter the host signal and add a watermark, thereby making the scheme nonadditive. The theory is applied to wavelet-based image watermarking. We find that, in this framework, additive watermarks are clearly suboptimal.

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The Parallel-Gaussian Watermarking Game

Cited by 41 publications

References 18 publications

Watermarking for Multimedia Security Using Complex Wavelets

Watermarking for Multimedia Security Using Complex Wavelets

Spread-Spectrum Substitution watermarking Game

Nonadditive Gaussian watermarking and its application to wavelet-based image watermarking

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