# Secure Spread Spectrum Watermarking for Multimedia by dffhrtcv3

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```									Secure Spread Spectrum
Watermarking for
Multimedia

Young K Hwang
The characteristics of watermark
 Unobtrusiveness
 Robustness
Common signal processing
Common geometric distortion
Collusion and forgery
 Universality
 Unambiguousness
Design for a strong watermark

 Watermark structure
i.i.d. samples from Gaussian distribution
 Insertion strategy
Embedded in perceptual frequency area

For a watermark to be robust and secure, these
two components must be designed correctly
Watermark in the frequency domain
Watermark
 The watermark is spread over many
frequency bins
   The location of watermark isn’t obvious
   Sufficient small to be undetectable

 Is it possible to verify watermark?
 The owner know where the watermark is
 Increase the energy at a particular freq to
detect the watermark.
Cox’s scheme: Embedding
Cox’s scheme: Detecting
Watermark procedure
 D : each document
 V=     v1 , v2 ,....., vn : a seq of D to be inserted by wmk
 X= x1 , x2 ,....., xn : a watermark to be inserted
 V’= v '1 , v '2 ,.....,   v 'n : watermarked sequence
 D’ : watermarked document
   D* : attacked document
     * : attacked watermarked seq of D*
V
   X * : attacked watermark
Inserting the watermark
 X      V = V’

 Three formulae for computing V’

v 'i  vi  xi        (1)
v'i  vi (1  xi )    (2)
v 'i  vi ( exi )   (3)
Extracting the watermark
 Find the inverse function of inserting watermark.

 (2)->            1  v 'i 
xi    1
  vi



Choosing the length of the Wmk
 The choice of n indicates the degree to which
the watermark is spread out among the
relevant components of the image.
 Proper value of n makes it easy to identify the
watermark.
 Too large value of n -> distort the image.
 Too small value of n -> cause robust problem
Evaluating the similarity of wmk
 The similarity of X and X* can be measured by

X*X
Sim( X , X ) 
*

X*X*

 To decide whether X and X* match, one determines
if Sim(X,X*) > T, where T=some threshold

 T : chosen to minimize the prob of both false alarm
and miss detections.
Evaluating the similarity of wmk Cont.
 Creator of X* has no information on X.
 X* is created independently to X.

*
 For fixed any xi , each x i will be independently
distributed according to N(0,1)
n

X X    ~ N (0,  xi* )  N (0, X *  X * ),
2
      *
i 1

 Thus,      Sim( X , X * ) ~ N (0,1)
 Thus, false alarm prob doesn’t depend on n
 But, the large n increases the value of similarity func.
Questions
 Why does large value of n increase similarity function
when X and X* are correlated?
x*  x  ei
n                 n
X  X   xi ( xi  ei )   xi2  xi ei
*

i 1              i 1
n
  E[ xi2  xi ei ]  n
i 1
n                        n
X  X   E( x  2 xi ei  e )  1  c  n(1  c)
*       *            2
i
2
i
i 1                        i 1

Thus, sim( X , X * ) ~      n
Post-processing options
 xi should be detected by similarity after many
kinds of signal processing.
 Some processes make it hard to detect
watermark due to severely distorting
watermark (for example, D/A-A/D, dithering
process)
 Setting T to low value result in increasing
false alarm prob.
 A method to increase sim(X,X*) is required for
some processes
Robust statistics for a specific
X*(distortion version of X)
*
 Goal : Increase Sim( X , X )
 increase     *
X X  decrease           X*X*

   Method 1)   xi*  xi*  Ei ( X * )
 xi* , if xi*  tolerance
   Method 2)   xi*                           
 0, otherwise            

   Method 3)   x  sign( x  Ei ( X ))
*
i
*
i
*
The original image   The dithered image
Question on previous slide
 Can such postprocessing steps affect the
false positive probability?

 According to Cox’s paper, that process
doesn’t affect the statistical significance
calculation as long as X* depends on D* and
D.
Resilience to Multiple Document
(Collusion) Attacks
 The most general attacks consists of using t multiple
watermarked copies D1'...,Dt' of document D to produce an un-
watermarked document D*.

 If the i-th watermark is the same for all copies of the document
then it cannot be detected, changed or removed.
Collution attack cont.
Marking copies of one document with a customer signature.

original

+
…
W1     W2                             WN

…                         N customers

Robust, secure, invisible watermark, resistant with respect
to the collusion attack (averaging copies of documents with
different marks).
Experimental Results

Response of the watermark
(ROW)=32.0
Experiment 1: Uniqueness of
Watermark
Experiment 2: Image Scaling

 To recover the watermark the quarter sized image was rescaled to
its original dimension, Fig. 7b.(ROW=13.4, 75% of the original data
is missing)
Experiment 3: JPEG Coding
Distortions

 Here are two JPEG encoded versions of the Bavarian couple Image
with different percentages for the quality and smoothing.
 ROW=22.8, 13.9 respectively
Experiment 4: Dithering Distortion

ROW=5.2, 10.5 with a postprocess
Experiment 5: Cropping

 Cropping involves the cutting out and removal of portions of an
image.(ROW=14.6, 75% of the original date is removed
Experiment 6: Print, Xerox, and Scan

 This image represents the result after it has gone through the 4
stage process, printing, xeroxing, scanning and rescaling.
 ROW=4.0 7.0 with a postprocess
Conclusion
 A need for electronic watermarking is developing as
electronic distribution of copyright material becomes
 This paper outlined the necessary characteristics of a
watermark
   Fidelity preservation
   Robustness to common signal and geometric
processing operations
   Robustness to attack
   Applicability to audio, image and video data.
Conclusion           …continued
 Using the Bavarian couple image, the algorithm used
can extract a reliable copy of the watermark from
imagery that was degraded with several common
geometric and signal processing procedures.
 These procedures include translation, rotation, scale
change, and cropping.
 The algorithm displays strong resilience to lossy
operations.
 Finally, this proposed methodology is used to hide
watermarks in data, the same process can be applied to
sending other forms of message through media data.

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