Digital Watermarking

Multimedia Security

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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

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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

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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.

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Invisible Watermark• Motivation

– The distribution of digital media is becoming faster, easier andrequiring 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

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Cryptology vs. Watermarking

• CryptologyOnce 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

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Watermarking Requirements

• Imperceptible

• Undeletable

• Statistically undetectable

• Robustness– resistant to lossy data compression– resistant to signal manipulation and

processing operation• Unambiguous

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Watermarked Image

Transmission

Corrupted Watermarked Image

Transmission

Lossy Compression

Geometric Distortions

Signal Processing

D/A - A/D Conversion

Typical Distortions or Intentional Tampering

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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

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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.

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Watermarking for Images & Videos

• Watermarking in

• Watermarking in

spatial domaintransform domainraw datacompressed data

• Detection/extraction the original datawith

without

• Watermarking withrandom number visually recognizable pattern

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LSB Flipping Method

• Generate the random walk sequence for each watermark (e.g.. 00112)• Force the LSB to match the watermark bit

0 1 2 3 4 5 0 1 2 3 4 5

Bit 1 0 55 73 7171

123 123 205 0

Bit 0 1 120121

123 70 72 147 199 1

Watermark 1 Bit 1 Bit 2 2 130 123123

67 6868

73 123 2

Watermark 2 Bit 3 3 140 133 120 72 7070

117 3

Bit 0 Bit 2 Bit 3 4 158159

142 123122

123 69 7170 4

5 195 178 150 112 67 70 5

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.

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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 = w1,...,wn

each wi is chosen according to zero-mean Gaussian Distributionthe image X is transform by full-frame DCT

n highest magnitude coefficients (except DC) are chosen: y1,...,yn

Embedding: y’i = yi + α wi

Extracting: wi = (yi* - yi) / α

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.

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Spread Spectrum Method (cont.)

OriginalImage

FFT/DCT

Determine Perceptually Significant Regions

WatermarkedImage

Inverse FFT/DCT

Watermark

FFT/DCT

OriginalImage

ReceivedImage

OriginalWatermark

ExtractedWatermark

－

Similar

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Spread Spectrum Method (cont.)

• Watermark detector

Watermark detector response to 1000 randomly generated watermarks

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Perceptually Masking Method

DetectionH0 : X = F* - F = NH1 : X = F* - F = W * + N

the hypothesis decision is obtained bysimilarity = correlation (X,W)

Spatial Masking

F

W

F’ WatermarkedImage

OriginalImage

m-sequence

DCT

Perceptual Analysis

DCT

+ IDCT

x

M. D. Swanson,”Transparent Robust Image Watermarking,” Proc. ICIP, pp. 211-214, Sep. 1996.

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Perceptually Masking Method (cont.)

• Frame from “pingpong”

• The watermark

Similarity value

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Digimarc Watermarking• A commercial watermarking software

– http://www.digimarc.com

Creator ID100024

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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

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Watermarking for Audio (cont.)

ExtractEnvelop

Quantization

M(w) +× ×

FrequencyMasking

InformationHanningWindow FFT

AudioSignal

PNsequence

ScaleFactor

w

w +originalsignal

• Watermark generator

Filtered PN-sequence

L. Boney, “Digital Watermarks for Audio Signals, “ IEEE Proc. Multimedia’96, pp. 473-480, 1996.

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Watermarking for Audio (cont.)

• Watermark detection

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Watermarking for Polygonal Models

• 3D models watermarking– vertex coordinates– vertex topology (connectivity)

Embedded pattern Simplified polygonal

R. Ohbuchi, “Watermarking 3-D Polygonal Models,” ACM Multimedia 97, pp. 261-272, 1997.

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Limitations of Watermarking

• Basic watermarking steps

Image I

Watermark WE I’

Image I

Test image J D W’ C

Watermark W

y/n ?

S. Craver, “Can Invisible Watermarks Resolve Rightful Ownerships?,” IBM Research Report, July, 1996.

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Limitations of Watermarking (cont.)

• Counterfeit

I

I’ D W C

Watermark W

y/n ?

Watermarked image I’ Dinv Counterfeit image I*

W*

I*

I’ D W* C

Watermark W*

y/n ?

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Visible watermark Invisible 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