Multiple Multiple Re-Watermarking Re-Watermarking

ScenariosScenarios

Severin Kampl, Daniel Mark

Multiple Re-Watermarking ScenariosMultiple Re-Watermarking Scenarios 22/22/22

Carinthia Tech Institute, University of Applied Sciences, Austria

Department of Computer Sciences, Salzburg University, Austria

Michael Michael DorferDorfer Severin Severin KamplKamplAlexander Alexander MaierMaier Daniel Daniel MarkMarkAndreas Andreas PalliPalli Günter Günter ScheerScheer Univ.-Prof. Mag. Dr. Andreas Univ.-Prof. Mag. Dr. Andreas UhlUhl

„„Multiple Re-Watermarking“ Multiple Re-Watermarking“ TeamTeam

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Presentation StructurePresentation Structure

IntroductionIntroduction Multiple Re-WatermarkingMultiple Re-Watermarking Experimental StudyExperimental Study Conclusion and PerspectivesConclusion and Perspectives

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DRM & multimedia securityDRM & multimedia security

Significantly different properties of Significantly different properties of Algorithms: Algorithms: Fragility (integrity investigations)Fragility (integrity investigations) Robustness (ownership claims)Robustness (ownership claims)

- Introduction- Introduction - Multiple Re- Watermarking- Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

IntroductionIntroduction

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Composite watermarkingComposite watermarking One single embedding processOne single embedding process

Segmented watermarkingSegmented watermarking Host data is partitionedHost data is partitioned

Successive watermarking (Re-Successive watermarking (Re-Watermarking)Watermarking) Embedding of one watermark after the otherEmbedding of one watermark after the other

Our focus: Multiple Re-Watermarking with Our focus: Multiple Re-Watermarking with robust techniquesrobust techniques

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

Multiple WatermarkingMultiple Watermarking

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Scenario for reconstruction of the trading chainScenario for reconstruction of the trading chain

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study- Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

Target ScenarioTarget Scenario

owner inforecipient info}

embedding technique

host image

1st sale re-sale re-sale . . . . . .

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Result:Result: Correlation value of (e.g. B with B‘) Correlation value of (e.g. B with B‘)

- Introduction- Introduction - Multiple Re- Watermarking- Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

Watermark DetectionWatermark Detection

Non-Blind AlgorithmNon-Blind Algorithm Correct reference image is requiredCorrect reference image is required

Blind AlgorithmBlind Algorithm No reference image is requiredNo reference image is required

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„„Lena“ Image Lena“ Image (512 x 512 Px, 8 bpp)(512 x 512 Px, 8 bpp)

Freely available watermarking Freely available watermarking toolboxtoolbox

Algorithms:Algorithms: Wang Wang (non-blind, waveletbased, MF - HF)(non-blind, waveletbased, MF - HF)

Corvi Corvi (non-blind, waveletbased NF - MF)(non-blind, waveletbased NF - MF)

Koch Koch (blind, DCT-based, random blocks)(blind, DCT-based, random blocks)

Final PSNR >= 38dbFinal PSNR >= 38db

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

Experimental Study: Experimental Study: SettingSetting

Lena image, 512x512 Pixels, 8bpp

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WANG - AlgorithmWANG - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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WANG - AlgorithmWANG - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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WANG - AlgorithmWANG - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

WANG - AlgorithmWANG - Algorithm

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WANG - AlgorithmWANG - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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CORVI - AlgorithmCORVI - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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CORVI - AlgorithmCORVI - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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Explanation:Explanation: Wang: Wang: most significant wavelet most significant wavelet

coefficientscoefficients

always different coefficientsalways different coefficients

Corvi: all approximation subband Corvi: all approximation subband coefficientscoefficients

less overwritingless overwriting

WANG WANG CORVI CORVI

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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KOCH - AlgorithmKOCH - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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KOCH - AlgorithmKOCH - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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KOCH - AlgorithmKOCH - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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KOCH - AlgorithmKOCH - Algorithm

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion / Perspectives - Conclusion / Perspectives

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WANG & KOCH as predictedWANG & KOCH as predicted CORVI as predicted when using CORVI as predicted when using

correct ref. Img.correct ref. Img. Corvi also useable in „blind“ wayCorvi also useable in „blind“ way

Large number of WMs detectableLarge number of WMs detectable Robustness concerning compressionRobustness concerning compression

- Introduction- Introduction - Multiple Re- Watermarking - Multiple Re- Watermarking - Experimental Study - Experimental Study

- Settings & Methods- Settings & Methods- Results- Results

- Conclusion & Perspectives - Conclusion & Perspectives

Conclusion & Conclusion & PerspectivesPerspectives

Thank you for your Attentention!Thank you for your Attentention!

Michael Dorfer, Severin Kampl, Alexander Maier, Daniel Michael Dorfer, Severin Kampl, Alexander Maier, Daniel Mark, Andreas Palli, Günter Scheer, Univ.-Prof. Mag. Dr. Mark, Andreas Palli, Günter Scheer, Univ.-Prof. Mag. Dr.

Andreas UhlAndreas Uhl