1. Protection of digital watermarking,
based on SVD against false positive
detection vulnerability
UNIVERSITY HADJ LAKHDER -BATNA-
SCIENCES FACULTY
COMPUTER SCIENCE DEPARTEMENT
By: Belferdi Wassila
Dr Behloul Ali
INTERNATIONAL CONFERENCE ON
ADVANCED COMMUNICATION AND
INFORMATION SYSTEMS
2. Plan
• Introduction:
• Singular Value Décomposition:
• False Positive Détection Vulnerability:
• Proposed Method:
• Sharing Secret Principle:
• Experiment Results :
• Robustness Conditions Of The Proposed Method:
• Conclusion and perspectives:
2
3. Introduction
• Day by day, the digital watermarking is becoming a
promising technique to protect digital data.
• It has seen numerous novel article covering new
techniques; each one of those techniques have there
advantages and inconveniences.
• In recent years, the techniques using linear algebra
has attracted attention of researchers to use it for
watermarking(e.g. SVD).
3
4. • From the viewpoint of linear algebra we can observe that.
a discrete image is an array of non-negative scalar entries
which may be regarded as a matrix.
M=USV’=S li UiVi
4
Singular Value Décomposition (1)
M U S V’
m
n
=
m r
n
5. 5
SVD Based Watermarking Example
Watermark
Hôst image
Uw
Sw
Vw
U
S
V
Insertion of
watermark in
hôst image
Watermarked
Image
6. False Positive Détection Vulnerability
• Duo to the watermark insertion method, another
watermark rather than the original can be reconstructed as
the embedded watermark; causing the false positive
detection vulnerability .
• If an attacker use U* and V* matrices of his own
watermark in place of reserved ones he can show his own
watermark.
6
8. Proposed Method
• To avoid that an attacker reconstruct his watermark
using their own matrices U* and V*; the idea is to share
a secret key D between matrices Uw, Sw and Vw of
watermark.
• During the embedding phase, for each matrices Uw, Sw
and Vw of watermark a key is inserted, then use the
modified S* to reconstruct the watermarked image,
those keys are calculated using sharing secret principle.
8
9. Sharing Secret Principle
• The goal is to divide a secret key D into pieces.
• The coefficients a1... ak-1 are randomly chosen from a uniform
distribution over the integers in [0, p-1]
• Pick a random k-1 degree polynomial q(x)=a0+alx+ . . . ak-1xk-1
in which a0=D.
• The values D1,..., Dn are evaluate:
D1= q(1) ,..., Di = q(i) ,..., Dn = q(n).
• Given any subset of k of these Di, we can find the
coefficients of q(x) by interpolation, and evaluate D=q (0).
9
12. Experiment Results
12
Robustness results of the proposed method against attacks
Attacks We W*e |D-Dc| |D-D*c|
Cropping 5 188037
Gaussian
noise 5 1888037
Rotation
0,2° 46568 234611
Resizing
44095 232139
Contrast
adjustment 425 188469
13. 13
Experiment Results(2)
the size
of
image
We W*e |D-Dc| |D-D*c|
512×512 5 188037
256×256 36 188007
128×128 913 187131
64×64 2406 185638
Results of the influence of image size on the robustness of the proposed method
14. Robustness Conditions Of The Proposed
Method
14
• In the SVD, the biggest
part of energy is
concentrated in low
frequencies of images,
the watermarking profit
this property to insert
watermark in low and
middle frequencies
according to
robustness/invisibility
compromiser
influence of the inserted secret on the quality of the watermarked image
15. Conclusion
• The novelty of our scheme is the use of the sharing secret
principle in watermark embedding, that is adaptively chosen
according to the local features of the image.
• The aim of our solution is to hide the watermark and insure
their robustness against the false positive detection
vulnerability.
• The experimental results obtained give evidence that our
scheme is robust against several attacks.
15
16. Perspectives
Our perspective turns around:
• increasing the robustness of our solution using block based
SVD scheme.
• Conceive a méthode to choose coefficients a1... ak-1 randomly
to obtain better results.
16
