1. Digital Watermarking Multimedia Security

2. 2 What is the Watermark ? Paper Watermark –the technique of impressing into the paper a form, image, or text to make forgery more difficult to record the manufacturer’s trademark

3. 3 Digital Watermark A digital watermark –a digital signal or pattern imposed on a digital document ( text, graphics, multimedia presentations ) visible watermark –the more obvious means of discouraging unauthorized use by reducing the commercial value of a document invisible watermark –the watermark is imperceptible to the human eye –when the ownership of data is in question, the watermark will then be extracted to characterize the ownership

4. 4 Visible Watermarking G. W. Braudaway, K. A. Magerlein and F. Mintzer, “Protecting publicly- available images with a visible watermark,” SPIE, vol. 2659, 1996, pp. 126-133.

5. 5 Invisible Watermark Motivation –The distribution of digital media is becoming faster, easier and requiring less effort to make exact copies How to protect the intellectual property? Conventional approaches –In analog world signature, steel seal, embossed portrait, copyright label... –In digital world: cryptology M encryption key E decryption key D M

6. 6 Cryptology vs. Watermarking Cryptology íOnce the data is decrypted, subsequent retransmission or dissemination is not encrypted Watermarking –Copyright information is hidden into digital data itself –Not restrict to access the data –Its objective is to permanently and unalterably reside in the data

7. 7 Watermarking Requirements Imperceptible Undeletable Statistically undetectable Robustness –resistant to lossy data compression –resistant to signal manipulation and processing operation Unambiguous

8. 8 Watermarked Image Transmission Corrupted Watermarked Image Transmission Lossy Compression Geometric Distortions Signal Processing D/A - A/D Conversion Typical Distortions or Intentional Tampering

9. 9 Watermark Embedding Making the watermark robustness is not trivial –with complete knowledge any watermark can theoretically be removed –with partial knowledge the removal may interfere with the viewing of the data the effort of removal is greater than the value of the data Challenges from data compression –Whatever hole one may find to fill with watermark is likely to be eliminated by data compression

10. 10 Watermarking for Text Line-Shift Coding Word-Shift Coding Feature Coding J.T. Brassil,”Electronic Marking and Identification Techniques to Discourage Document Copying,” IEEE JSAC, vol 13, no.8, Oct, 1995.

11. 11 Watermarking for Images & Videos Watermarking in spatial domain transform domain raw data compressed data Detection/extraction the original data with without Watermarking with random number visually recognizable pattern

12. 12 LSB Flipping Method Generate the random walk sequence for each watermark (e.g.. 0011 2 ) Force the LSB to match the watermark bit m This works will not survive any modification S. Walton, “Image Authentication for a Slippery New Age,” Dr. Dobb’s Journal, pp. 18-26, April 1995.

13. 13 Spread Spectrum Method Spread spectrum coding of a watermark –frequency domain of the image communication channel –watermark the signal transmitted through the channel the watermark W = w 1,...,w n each w i is chosen according to zero-mean Gaussian Distribution the image X is transform by full-frame DCT n highest magnitude coefficients (except DC) are chosen: y 1,...,y n Embedding: y ’ i = y i +  w i Extracting: w i = (y i * - y i ) /  similarity = correlation (W,W * ) I. J. Cox,”Secure Spread Spectrum Watermarking for Multimedia,” IEEE Trans. IP, vol 6, no.12, pp. 1673-1687, Dec. 1997.

14. 14 Spread Spectrum Method (cont.) Original Image FFT/DCT Determine Perceptually Significant Regions Watermark Watermarked Image Inverse FFT/DCT FFT/DCT Original Image Received Image Original Watermark Extracted Watermark － Similar

15. 15 Spread Spectrum Method (cont.) Watermark detector Watermark detector response to 1000 randomly generated watermarks

16. 16 Perceptually Masking Method o Detection H 0 : X = F * - F = N H 1 : X = F * - F = W * + N the hypothesis decision is obtained by similarity = correlation (X,W) Spatial Masking F W F’ Original Image Watermarked Image m-sequence DCT Perceptual Analysis DCT + IDCT x M. D. Swanson,”Transparent Robust Image Watermarking,” Proc. ICIP, pp. 211-214, Sep. 1996.

17. 17 Perceptually Masking Method (cont.) Frame from “pingpong” The watermark Similarity value

18. 18 Digimarc Watermarking A commercial watermarking software –http://www.digimarc.com Creator ID 100024

19. 19 Watermarking for Audio Phase Coding –Inserting the watermark by modifying the phase of each frequency component Spread Spectrum Method –The watermark code is spread over the available frequency band, and then attenuated and added as additive random noise Perceptual Method –The watermark is generated by filtering a PN-sequence with a filter that approximates the frequency masking characteristics of HAS –Weighting the watermark in the time domain to account for temporal masking

20. 20 Watermarking for Audio (cont.) Watermark generator Filtered PN-sequence L. Boney, “Digital Watermarks for Audio Signals, “ IEEE Proc. Multimedia’96, pp. 473-480, 1996.

21. 21 Watermarking for Audio (cont.) Watermark detection

22. 22 Watermarking for Polygonal Models 3D models watermarking –vertex coordinates –vertex topology (connectivity) Embedded patternSimplified polygonal R. Ohbuchi, “Watermarking 3-D Polygonal Models,” ACM Multimedia 97, pp. 261-272, 1997.

23. 23 Limitations of Watermarking Basic watermarking steps Image I Watermark W E I’I’ Image I Test image J D W’W’ C Watermark W y/n ? S. Craver, “Can Invisible Watermarks Resolve Rightful Ownerships?,” IBM Research Report, July, 1996.

24. 24 Limitations of Watermarking (cont.) Counterfeit I I’I’ D W C Watermark W y/n ? Watermarked image I ’ D inv Counterfeit image I * W*W* I*I* I’I’ D W*W* C Watermark W * y/n ?

25. 25 Visible watermarkInvisible watermark Random sequence watermark Visually recognizable watermark Digital watermark Watermark : Verification : ID number (random number) Quantitative measurement of the detection Visually recognizable pattern Extracted pattern & Quantitative measurement