Paper Explaination : A Survey of Digital Watermarking Techniques, Applications and Attacks A paper by Prabhishek Singh, R S Chadha

By Samarth GodaraRoll no. 14223004

Mtech 1st sem. NITJ, Punjab

Summary of

A Survey of Digital Watermarking Techniques, Applications and Attacks

A paper by Prabhishek Singh, R S Chadha

By Samarth GodaraRoll no. 14223004

Mtech 1st sem. NITJ, Punjab

Summary of

A Survey of Digital Watermarking Techniques, Applications and Attacks

A paper by Prabhishek Singh, R S Chadha

PaperIntroduction

Digital Watermarking Technology

WatermarkingTechniques

Digital WatermarkingApplications

WatermarkingAttacks

Challenges and

LimitationsOf Digital

Watermarking

Performance Evaluation

Metric

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking


Metric

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking


Metric● Definition● Need

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking



● Classification● Features● Performance Factor● Architecture of Digital

Watermarking● Styles of Robust

Watermarks

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks

● Spatial Domain● Additive Watermarking● LSB● SSM Modulation● Texture Mapping Coding● Patchwork Algo● Correlation Based

● Frequency Domain● DCT● DWT● DFT

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks



● Copyright Protection● Copy Protection● Digital Right Management● Tamper Proofing● Broadcast Monitering● Fingerprinting● Access Control● Medical Application● Image and Content Authentication● Annotation and privacy control● Media Forensics● Communication Enhancement● Content Protection● Content Filtering● Communication of ownership

and objects● Document Security● Locating Content Online● Audience Measurement● Improved Auditing

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks





● Removal Attack● Interference Attack● Geometric Attack● Low pass filtering attack● Forgery Attack● Security Attack● Protocol Attack● Cryptographic Attack● Active Attack● Passive Attack● Collusion Attacks● Image Degradation● Image Enhancement● Image Compression● Image Transformation

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks






● Properties of Visual Signal● Non Stationary● Periodicity

● Properties of HVS● Brightness Sensitivity

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks







● Properties of HVS● Brightness Sensitivity

● MSE● SNR● PSNR● BER

Introduction

Introduction✗ The success of the Internet, cost-effective and popular digital ✗ recording and storage devices, and the promise of higher bandwidth ✗ and quality of service for both wired and wireless networks have ✗ made it possible to create, replicate, transmit, and distribute digital✗ content in an effortless way. The protection and enforcement of ✗ intellectual property rights for digital media has become an ✗ important issue.

Introduction✗ The success of the Internet, cost-effective and popular digital ✗ recording and storage devices, and the promise of higher bandwidth ✗ and quality of service for both wired and wireless networks have ✗ made it possible to create, replicate, transmit, and distribute digital✗ content in an effortless way. The protection and enforcement of ✗ intellectual property rights for digital media has become an ✗ important issue. ● Digital watermarking is that

technology that provides and ensures security, data authentication and copyright protection to the digital media.



● Digital watermarking is the embedding of signal, secret information (i.e. Watermark) into the digital media such as image, audio and video. Later the embedded information is detected and extracted out to reveal the real owner/identity of the digital media.




● Watermarking is used for following reasons, Proof of Ownership (copyrights and IP protection), Copying Prevention, Broadcast Monitoring, Authentication, Data Hiding.

IntroductionThe success of the Internet, cost-effective and popular digital recording and storage devices, and the promise of higher bandwidth and quality of service for both wired and wireless networks have made it possible to create, replicate, transmit, and distribute digital content in an effortless way. The protection and enforcement of intellectual property rights for digital media has become an important issue. ● Digital watermarking is that



● Watermarking is used for following reasons, Proof of Ownership (copyrights and IP protection), Copying Prevention, Broadcast Monitoring, Authentication, Data Hiding.

● Watermarking consists of two modules watermark embedding module and watermark detection and extraction module.

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks







● Propoerties of HVS● Brightness Sensitivity


Digital Watermark Technology

Classification

Classification

ClassificationRobustness1)Robust Ex- DCT2)Fragile Ex - LSB3)Semi-Fragile


According to Attached media1)Image Watermarking2)Video Watermarking3)Audio Watermarking4)Text Watermarking5)Graphic Watermarking



According to Perceptivity1)Visible Watermark2)Invisible Watermark




According to purpose1) Copyright Protection Watermark2) Tampering tip Watermarking3) Anti-Counterfieting Watermarking4) Anonymous Mark Watermarking





According to Watermark type1)Noise Type2)Image Type






According to Domain1)Spatial Domain2)Frequency Domain







According to Detection Process1)Visual Watermarking2)Semi-Blind Watermarking3)Blind Watermarking







According to Detection Process1)Visual Watermarking2)Semi-Blind Watermarking3)Blind Watermarking

According to Use of keys1)Asymmetric Watermarking2)Symmetric Watermarking

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Features of Digital Watermarking



Robustness


Robustness

Imperceptibility


Robustness

Imperceptibility

Security


Robustness

Imperceptibility

Security

Verifiability


Robustness

Imperceptibility

Security

Verifiability

Capacity and data payload


Robustness

Imperceptibility

Security

Verifiability


Computational Cost


Robustness

Imperceptibility

Security

Verifiability


Computational Cost

Watermark Detection reliability


Robustness

Imperceptibility

Security

Verifiability


Computational Cost


Blind or Non-Blind Detection of watermark


Robustness

Imperceptibility

Security

Verifiability


Computational Cost


Blind or Non-Blind Detection of watermark

Tradeoff between performance factors

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking



● Classification● Features● Requirements● Architecture of Digital


Watermarks









Requirements of Digital Watermarking



Robustness


Robustness

Security


Robustness

Security

Capacity


Robustness

Security

Capacity

Perceptivity


Robustness

Security

Capacity

Perceptivity

Modification and Multiple watermarks


Robustness

Security

Capacity

Perceptivity

Modification and Multiple watermarks

Invertibility

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Architecture of Digital Watermark



PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Styles of Robust Watermarks



Noise Watermark


Noise Watermark

Logo Watermark


Noise Watermark

Logo Watermark Message Watermark

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Watermarking Techniques

Spatial Domain

Spatial Domain

Spatial Domain

Additive Watermarking

Spatial Domain


Least Significant Bit

Spatial Domain



SSM Modulation Based Technique

Spatial Domain




Spatial Domain




Texture mappingtechnique

Spatial Domain





Patchwork Algorithm

Patchwork Algorithm

Patchwork Algorithm

1 14 2 15 3

16 4 17 5 18

6 19 7 20 8

21 9 22 10 23

11 24 12 25 13

Image

Patchwork Algorithm

1 14 2 15 3

16 4 17 5 18

6 19 7 20 8

21 9 22 10 23

11 24 12 25 13

Image

0

1

1

Watermark

Patchwork Algorithm

1 14 2 15 3

16 4 17 5 18

6 19 7 20 8

21 9 22 10 23

11 24 12 25 13

Image

0

1

1

Watermark

3 1

3 2

5 3

4 2

1 1

5 4

Randomly Seleted Patches

Patch A Patch B

Patchwork Algorithm

1 14 2 15 3

16 4 17 5 18

6 19 7 20 8

21 9 22 10 23

11 24 12 25 13

Image

0

1

1

Watermark

3 1

3 2

5 3

4 2

1 1

5 4


Patch A Patch B

5-2 3

1-17 -16

23-8 15

Distances between the pixels

3

-16

15



Patchwork Algorithm

1 14 2 15 3

16 4 17 5 18

6 19 7 20 8

21 9 22 10 23

11 24 12 25 13

Image

0

1

1

Watermark

3 1

3 2

5 3

4 2

1 1

5 4


Patch A Patch B

5-2 3

1-17 -16

23-8 15


3

-16

15



Swap 4,2 – 3,1Swap 1,1 – 3,2Don't Swap 5,4 – 5,3

Patchwork Algorithm

17 14 5 15 3

16 4 1 2 18

6 19 7 20 8

21 9 22 10 23

11 24 12 25 13

Watermarked Image

0

1

1

Watermark

3 1

3 2

5 3

4 2

1 1

5 4


Patch A Patch B

5-2 3

1-17 -16

23-8 15


3

-16

15



Swap 4,2 – 3,1Swap 1,1 – 3,2Don't Swap 5,4 – 5,3

Spatial Domain





Patchwork Algorithm

Spatial Domain





Patchwork Algorithm

Correlation Based Technique

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Frequency Domain

A Brief Overview of Frequency Domain Concepts

Fourier Transform

● The Fourier transform is used to express an image in the spatial intensity domain as a sum of sine waves in the frequency domain.

● The spectrum consists of the frequency amplitudes of the sin waves that represent the image.

● The frequency spectrum image is symmetric about its center. The lowest or zero frequency wave amplitude found in an image is located at the center of the frequency spectrum image.

● Frequency increases from low to high as you move from the center to the corner of the spectrum image.

The yellow dot in the center of the spectrum is the amplitude of the zero frequency wave or direct current (DC) of the constant yellow image and is the average

color of the image.

A horizontal line profile shown on the left shows the sine wave with frequency 4. A vertical line profile is always a constant line with zero frequency.

Four pixels to the left and right of the bright center DC pixel are two bright pixels which are the amplitude of the sine wave of frequency 4 found in the image.

● A horizontal sine wave with 16 cycles shown on left again shows 3 bright pixels in its spectrum image on right but the bright pixels are further apart. In this case the two bright pixels are spaced 16 pixels to the left and right side of the bright center DC pixel.

● If the width of the image is divided by the frequency or distance of the two bright pixels from the center DC pixel you will get the wavelength or distance between peaks of the sin wave contained in the image.

● In the above example the image width of 128 pixels is divided by 16 cycles to yield a wavelength of 8 pixels between each vertical band.

If the horizontal sine wave image with frequency 16 is rotated 90 degrees then the two bright pixels are above and below the center bright DC pixel. In this case a vertical line profile shown on the left shows the sine wave with frequency 16.

● If the horizontal sine wave image with frequency 16 is rotated 45 degrees then the two bright pixels are on a 45 degree line through the center bright DC pixel.

● But now both a horizontal and vertical line profile show a sine wave of frequency 11. Since spectrum frequency amplitudes are computed and displayed with respect to the width and height the spectrum is a blend of the horizontal and vertical sine waves of frequency 11.

● The two bright pixels on the 45 degree line through the center DC pixel are now 11 pixels from the center of the spectrum.

The spectrum of an artificial star of radius 3 is shown above.

Below is the same star shifted to the lower right with its spectrum.

Note that the spectrum does not change when the position of the star is shifted since the frequency spectrum only contains frequency amplitude information and not position information.

The Fourier transform of the star image computed by the Frequency Filter actually computes a frequency amplitude spectrum and also a phase image that contains position information.

Discrete Wave Transform

Discrete Wave TransformIn numerical analysis and functional analysis, a discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled.

As with other wavelet transforms, a key advantage it has over Fourier transforms is temporal resolution: it captures both frequency and location information.


Continuous Image Vertical DWT of the image



Discrete Cosine Transform

DCT like a Fourier image Transform, it represents data in terms of frequency space rather than an amplitude space.

DCT based watermarking techniques are robust compared to spatial domain techniques. Such algorithms are robust against simple image processing operations like low pass filtering, brightness and contrast adjustment, blurring etc.

However, they are difficult to implement and are computationally more expensive.

At the same time they are weak against geometric attacks like rotation, scaling, cropping etc.

DCT domain watermarking can be classified into Global DCT watermarking and Block based DCT watermarking.

Embedding in the perceptually significant portion of the image has its own advantages because most compression schemes remove the perceptually insignificant portion of the image.

Discrete Cosine Transform

Steps to Embed the DCT watermark

Discrete Wavelet transform

In numerical analysis and functional analysis, a discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled.

As with other wavelet transforms, a key advantage it has over Fourier transforms is temporal resolution: it captures both frequency and location information.

The wavelet transform decomposes the image into three spatial directions, i.e. horizontal, vertical and diagonal. Hence wavelet reflects the anistropic properties of Human visual system more precisely.

Advantage of DWT over DCT

- DWT understands the HVS more closely that the DCT.

- Image can be shown at different levelsof the resolution and processed from low level to high level.

Disadvantage of DWT over DCT

- Computational cost is more of DWT.

Discrete Fourier Transform


Transforms a continuous function into its frequency components

Robust against geometric attacksRotationScalingCroppingTranslation


Transforms a continuous function into its frequency components

Robust against geometric attacksRotationScalingCroppingTranslation

Advantage of DFT over DWT and DCT

- DFT is rotation, scaling and translation invariant.

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Digital Watermarking Applications


Copyright Protection



Copy Protection



Copy Protection

Digital Right Management



Copy Protection


Tamper Proofing



Copy Protection


Tamper Proofing

Broadcast Monitoring



Copy Protection


Tamper Proofing


Fingerprinting



Copy Protection


Tamper Proofing


Fingerprinting

Access control



Copy Protection


Tamper Proofing


Fingerprinting

Access control

Medical Application



Copy Protection


Tamper Proofing


Fingerprinting

Access control

Medical Application

Image and content Authentication



Annoation and privacy control



Media Forensics



Media Forensics

Communicaiton Enhancement



Media Forensics


Content Protection



Media Forensics


Content Protection

Content Filtering



Media Forensics


Content Protection

Content Filtering

Communication of Ownership and contents



Media Forensics


Content Protection

Content Filtering


Document and image security



Media Forensics


Content Protection

Content Filtering



Locating content online



Media Forensics


Content Protection

Content Filtering




Audience Measurement



Media Forensics


Content Protection

Content Filtering




Audience Measurement

Imporved Auditing

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Watermarking Attacks


Removal Attack


Removal Attack

Interference Attack


Removal Attack

Interference Attack

Geometric Attack


Removal Attack

Interference Attack

Geometric Attack

Low pass filtering attack


Removal Attack

Interference Attack

Geometric Attack


Forgery Attack


Removal Attack

Interference Attack

Geometric Attack


Forgery Attack

Security Attack



Protocol Attack


Protocol Attack

Cryptographic attack


Protocol Attack


Active Attack


Protocol Attack


Active Attack

Passive attack


Protocol Attack


Active Attack

Passive attack

Collusion Attack


Protocol Attack


Active Attack

Passive attack

Collusion Attack

Image Degradation


Protocol Attack


Active Attack

Passive attack

Collusion Attack

Image Degradation

Image Enhancement


Protocol Attack


Active Attack

Passive attack

Collusion Attack

Image Degradation

Image Enhancement

Image Compression


Protocol Attack


Active Attack

Passive attack

Collusion Attack

Image Degradation

Image Enhancement

Image Compression

Image Transformation

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Challenges and limitations of digital watermarking

Visual Signals are generally recognized as amplitude plots, intensity versus space displays of images information and intensity verses space and time display of video scenes.



Properties of Visual Signal

Non-stationary – preserve the edges, use the texture part to store additional information









Periodicity – Exploit the redundancy between the frames and lines to store the watermark information





Periodicity – Exploit the redundancy between the frames and lines to store the watermark information



The visibility of distortion depends on the background texture.

The distortion visibility is low when the background has a strong texture.







Weber's Law

If you lift up and hold a weight of 2.0 kg, you will notice that it takes some effort. If you add to this weight another 0.05 kg and lift, you may not notice any difference between the apparent or subjective weight between the 2.0 kg and the 2.1 kg weights. If you keep adding weight, you may find that you will only notice the difference when the additional weight is equal to 0.2 kg. The increment threshold for detecting the difference from a 2.0 kg weight is 0.2 kg. The just noticeable difference (jnd) is 0.2 kg.




Weber's Law


Now start with a 5.0 kg weight. If you add weight to this, you will find that the just noticeable difference is 0.5 kg. It takes 0.5 kg added to the 5.0 kg weight for you to notice an apparent difference.

For the weight of magnitude, I, of 2.0 kg, the increment threshold for detecting a difference was a I (pronounces, delta I) of 0.2 kg.

For the weight of magnitude, I = 5.0 kg, the increment threshold I = 0.5 kg.




Weber's Law


Now start with a 5.0 kg weight. If you add weight to this, you will find that the just noticeable difference is 0.5 kg. It takes 0.5 kg added to the 5.0 kg weight for you to notice an apparent difference.

For the weight of magnitude, I, of 2.0 kg, the increment threshold for detecting a difference was a I (pronounces, delta I) of 0.2 kg.

For the weight of magnitude, I = 5.0 kg, the increment threshold I = 0.5 kg.

The ratio of I/I for both instances (0.2/2.0 = 0.5/5.0 = 0.1) is the same. This is Weber's Law.

PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









Performance Evaluation Metric


Mean Square Error (MSE)



{ Each pixel [ (difference)^2) ] }----------------------------------------

Total Number of pixelsMSE =



Signal to noise ratio (SNR)




SNR = 10 X Number of digits of (Ratio of original signal over the noise in it)




Peak Signal to Noise Ratio (PSNR)

PSNR = 10 log 10 (L*(L/MSE))L = peak signal

Ex -> L =255 for 8bit pixel





PSNR = 10 log 10 (L*(L/MSE))L = peak signal

Ex -> L =255 for 8bit pixel

PSNR = 10 x Number of digits ( peak value X ( peak value / mean sq. error ))





Bit Error Ratio (BER)






BER = P/ (H*W)H and W are height and width of the watermarked image. P isthe count number initialized to zero and it increments by one

if there is any bit difference between cover and embed image.






BER = P/ (H*W)H and W are height and width of the watermarked image. P isthe count number initialized to zero and it increments by one

if there is any bit difference between cover and embed image.

BER = number of changed bits / total size of the image






PaperIntroduction




WatermarkingAttacks

Challenges and


Watermarking





Watermarks









THE END

THE END

Time to wake up...!!!

THE END

Time to wake up...!!!

Thank You...

Engineering

Paper Explaination : A Survey of Digital Watermarking Techniques, Applications and Attacks A paper by Prabhishek Singh, R S Chadha