DIGITAL WATERMARKING Ngô Huy Phúc Trần Kim Lân Phạm Quốc Hiệp

PART 1 INTRODUCTION

STEGANOGRAPHY Steganography (art of hidden writing) – The art and science of writing hidden messages in such a way that no one apart from the intended recipient knows of the existence of the message. – The existence of information is secret.

Histaeus used his slaves (information tattooed on a slave’s shaved head) Initial Applications of information hiding  Passing Secret messages STEGANOGRAPHY

Physical steganography

STEGANOGRAPHY Digital steganography Network steganography

DEFINITION The process of embedding information into a digital signal in a way that is difficult to remove. The signal may be text, images, audio, video. The information is also carried in the copy if the signal is copied.

DEFINITION Example:

GENERAL APPLICATIONS Copyright Protecton To prove the ownership of digital media.

Tamper proofing To find out if data was tampered. GENERAL APPLICATIONS

Quality Assessment Degradation of Visual Quality Loss of Visual Quality GENERAL APPLICATIONS

LIFE-CYCLE PHASES Attemp to extract watermark from signal The marked signal is modified Produce watermarked signal

CLASSIFICATION Digital watermarking techniques can be classified in many ways : Visibility Robustness Perceptibility Capacity Embedding method

VISIBILITY Visible – Text or a logo which identifies the owner of the media. Invisible – Information is added as digital data to audio, picture or video, but it cannot be perceived. – May be a form of Steganography.

ROBUSTNESS Robust – Resisted a designated a class of transformations. – Against adversary based attack. (e.g. noise addition to images) – Used in copy protection application. Example: Robust Private Spatial Watermarks

ROBUSTNESS Fragile – Fail to be detected after the slightest modification. – Used for tamper detection. Example: Blind Fragile DCT based Watermarks

ROBUSTNESS Semi-fragile – Resist benign tramsformations but fails detection after malignant transformations. – Robust against user-level operation. (e.g. image compression) – Used for detect malignant transformation. Example: Blind Semi-fragile Spatial Watermarks

PERCEPTIBILITY Perceptible – Its presence in the marked signal is noticable, but non-intrusive. Imperceptible – Original cover signal and the marked signal are close to perceptually indistinguishable.

PERCEPTIBILITY Stanford Bunny 3D Model Visible Watermarks in Bunny Model  Distortion Watermarking Stanford Bunny 3D Model Watermarking Invisible Watermarks in Bunny Model  Minimal Distortion

CAPACITY Depend on the length of the embedded message. Zero-bit long – Detect the presence or absence of the watermark. – A 1 denotes the presence. 0 denotes the absence. N-bit long – Modulated in the watermark. – Support multiple watermarks.

EMBEDDING METHOD Spread-spectrum – The marked signal is ontained by an additive modification. – Modestly robust. – Have a low information capacity.

EMBEDDING METHOD Quantization type – The marked signal is ontained by quantization – Low robustness. – Have a high infoirmation capacity. Amplitude modulation – The marked signal is ontained by additive modification similar to spread spectrum method. – Embedded in the spatial domain.

As much information (watermarks) as possible.  Capacity Only be accessible by authorized parties.  Security Resistance against hostile/user dependent changes  Robustness Invisibility  Imperceptibility DESIGN REQUIREMENTS

PART 2 SPECIFIC WATERMARKING TECHNIQUES ON IMAGES

A very simple yet widely used technique for watermarking images is to add a pattern on top of an existing image. Usually this pattern is an image itself - a logo or something similar. SIMPLE WATERMARKING

The LSB technique is the simplest technique of watermark insertion. Consider a still image : each pixel of the color image has three components — red, green and blue. Allocate 3 bytes for each pixel. Then, each colour has 1 byte, or 8 bits. LSB : LEAST SIGNIFICANT BIT

A pixel that is bright purple in colour can be showN as X0 = {R=255, G=0, B=255} Look at another pixel: X1 = {R=255, G=0, B=254} Detecting a difference of 1 on a color scale of 256 is almost impossible for human eye.  Replace the color intensity information in the LSB with watermarking information, the image will still look the same to the naked eye. LSB : LEAST SIGNIFICANT BIT

Use a secret key to choose a random set of bits. The more bits used in the host image, the more it deteriorates. Increasing the number of bits used though obviously has a beneficial reaction on the secret image increasing its clarity. LSB : LEAST SIGNIFICANT BIT

Host image is on the left, watermark image is on the right LSB : LEAST SIGNIFICANT BIT

Watermarking in the frequency domain involves selecting the pixels to be modified based on the frequency of occurrence of that particular pixel. Transform an image into the frequency domain. A block-based DCT watermarking approach is implemented. An image is first divided into blocks and DCT is performed on each block. The watermark is then embedded by selectively modifying the middle- frequency DCT coefficients. FREQUENCY-BASED TECHNIQUES

What is DCT ? Formally, the discrete cosine transform (DCT) is a linear, invertible function F : R N -> R N (where R denotes the set of real numbers), or equivalently an invertible N × N square matrix FREQUENCY-BASED TECHNIQUES

Discrete wavelet transform (DWT) The image is separated into different resolution The original image is high-pass filtered, yielding the three large images, each describing local changes details in the original image It is then low-pass filtered and downscaled, yielding an approximation image. This image is high-pass filtered to produce the three smaller detail images. And low-pass filtered to produce the final approximation image in the upper-left. WAVELET WATERMARKING TECHNIQUES

Embedding the watermark The host image and watermark are transformed into wavelet domain. The transformed watermark coefficients were embedded into those of host image at each resolution level with a secret key. WAVELET WATERMARKING TECHNIQUES

A Narrow-band signal is transmitted over a much larger bandwidth such that the signal energy presented in any signal frequency is undetectable A watermark is spread over many frequency bins so that the energy in one bin is very small and certainly undetectable. SPREAD-SPECTRUM TECHNIQUES

Because the watermark verification process knows the location and content of the watermark, it is possible to concentrate these weak signals into a single output with high SNR ( Signal-to-noise ratio). Remark – To destroy such a watermark would require noise of high amplitude to be added to all frequency bins. – The location of the watermark is not obvious. – Frequency regions should be selected that ensures degradation of the original datafollowing any attack on the watermark. SPREAD-SPECTRUM TECHNIQUES

References Techniques and Applications of Digital Watermarking and Content Protection Michael Arnold, Martin Schmucker, Stephen D. Wolthusen Steganography And Digital Watermarking Jonathan Cummins, Patrick Diskin, Samuel Lau and Robert Parlett, School of Computer Science, The University of Birmingham. Real-Time Digital Image Watermarking Subramaniam Ganesan, Professor of Oakland University, Michigan

PART 3 ATTACKING METHODS

Foundations of Attacking 3 effects make detection of watermarking useless: – Watermark cannot be detected. – False watermarks are detected. – Unauthorized detection of watermark.

Classification of Attacking Removal attacks Geometrical attacks Cryptographic attacks Protocol attacks

Classification of watermarking attacks

Removal Attacks Most obvious method Aim for complete removal of watermarking Extreme form of this type is restore the original object Can happen unintentionally due to operations in some certain applications.

Geometrical Attacks Do not actually remove the embedded watermark Intend to distort the watermark detector synchronization with the embedded information

Cryptographic Attacks Aim at cracking the security methods in watermarking schemes Finding a way to remove the embedded watermark information Embed misleading watermarks High computational complexity

Protocol Attacks Aim at attacking the entire concept of the watermarking application First proposed in framework of invertible watermark The attacker subtracts his own watermark from the watermarked data and claims to be the owner Another type is copy attack

Some Methods Collusion Attack – Estimate the watermark from different works with same watermark – The attackers can obtain an approximation of the watermark by averaging the watermarked works

Some Methods Remodulation Attack Damage watermark base on watermark estimation

Some Methods Copy Attack Estimate a watermark from watermarked data and copy it to some other data