Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

Digital audio, video, images, and documents are flying through cyberspace to their respective owners. Unfortunately, along the way, individuals may choose to intervene and take this content for themselves. Digital watermarking and steganography technology greatly reduces the instances of this by limiting or eliminating the ability of third parties to decipher the content that he has taken. The many techiniques of digital watermarking (embedding a code) and steganography (hiding information) continue to evolve as applications that necessitate them do the same. The authors of this second edition provide an update on the framework for applying these techniques that they provided researchers and professionals in the first well-received edition. Steganography and steganalysis (the art of detecting hidden information) have been added to a robust treatment of digital watermarking, as many in each field research and deal with the other. New material includes watermarking with side information, QIM, and dirty-paper codes. The revision and inclusion of new material by these influential authors has created a must-own book for anyone in this profession.

*This new edition now contains essential information on steganalysis and steganography
*New concepts and new applications including QIM introduced
*Digital watermark embedding is given a complete update with new processes and applications

Digital Watermarking and Steganography

Sphere Packings, Lattices and Groups

Review: Digital image steganography: Survey and analysis of current methods

We describe a novel general strategy for building steganography detectors for digital images. The process starts with assembling a rich model of the noise component as a union of many diverse submodels formed by joint distributions of neighboring samples from quantized image noise residuals obtained using linear and nonlinear high-pass filters. In contrast to previous approaches, we make the model assembly a part of the training process driven by samples drawn from the corresponding cover- and stego-sources. Ensemble classifiers are used to assemble the model as well as the final steganalyzer due to their low computational complexity and ability to efficiently work with high-dimensional feature spaces and large training sets. We demonstrate the proposed framework on three steganographic algorithms designed to hide messages in images represented in the spatial domain: HUGO, edge-adaptive algorithm by Luo , and optimally coded ternary ±1 embedding. For each algorithm, we apply a simple submodel-selection technique to increase the detection accuracy per model dimensionality and show how the detection saturates with increasing complexity of the rich model. By observing the differences between how different submodels engage in detection, an interesting interplay between the embedding and detection is revealed. Steganalysis built around rich image models combined with ensemble classifiers is a promising direction towards automatizing steganalysis for a wide spectrum of steganographic schemes.

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Rich Models for Steganalysis of Digital Images

Digital watermarking was introduced at the end of the 20th century to provide means of enforcing copyright protection once the use and distribution of digital multimedia data have exploded. This technology has first been intensively investigated for still images and recent efforts have been put to exhibit unifying characteristics. On the other hand, the situation is rather different in the context of video watermarking, where unrelated articles are scattered throughout the literature. The purpose of this paper is consequently to give an in-depth overview of video watermarking and to point out that it is not only a simple extension of still images watermarking. New applications have to be considered, specific challenges have to be taken up and video-driven approaches have to be investigated.

A guide tour of video watermarking

We describe a new watermarking system based on the principles of informed coding and informed embedding. This system is capable of embedding 1380 bits of information in images with dimensions 240/spl times/368 pixels. Experiments on 2000 images indicate the watermarks are robust to significant valumetric distortions, including additive noise, low-pass filtering, changes in contrast, and lossy compression. Our system encodes watermark messages with a modified trellis code in which a given message may be represented by a variety of different signals, with the embedded signal selected according to the cover image. The signal is embedded by an iterative method that seeks to ensure the message will not be confused with other messages, even after addition of noise. Fidelity is improved by the incorporation of perceptual shaping into the embedding process. We show that each of these three components improves performance substantially.

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Applying informed coding and embedding to design a robust high-capacity watermark

Watermarking digital video material is usually considered as watermarking a sequence of still images. However, such a frame-by-frame approach is very risky since straightforward embedding strategies can result in poor performance in terms of security i.e., against hostile attacks. As examples, two very common video-watermarking systems will be presented as well as the associated intra-video collusion attacks which defeat them. Then, both watermark modulation and embedding strength modulation will be surveyed to design alternative embedding strategies which exhibit superior performance against such attacks. Nevertheless, it will also be shown that an expert attacker can still construct an effective watermark removal attack. Finally, there will be a discussion to assert whether or not security against intra-video collusion can be achieved with such blind frame-by-frame embedding strategies.

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Security pitfalls of frame-by-frame approaches to video watermarking

We propose a new method to detect resampled imagery. The method is based on examining the normalized energy density present within windows of varying size in the second derivative of the image in the frequency domain, and exploiting this characteristic to derive a 19-D feature vector that is used to train a SVM classifier. Experimental results are reported on 7500 raw images from the BOSS database. Comparison with prior work reveals that the proposed algorithm performs similarly for resampling rates greater than 1, and is superior to prior work for resampling rates less than 1. Experiments are performed for both bilinear and bicubic interpolations, and qualitatively similar results are observed for each. Results are also provided for the detection of resampled imagery with noise corruption and JPEG compression. As expected, some degradation in performance is observed as the noise increases or the JPEG quality factor declines.

Normalized Energy Density-Based Forensic Detection of Resampled Images

A number of analogies to cryptographic concepts have been made about watermarking. In this paper, we argue that these analogies are misleading or incorrect, and highlight several analogies to support our argument. We believe that the fundamental role of watermarking is the reliable embedding and detection of information and should therefore be considered a form of communications. We note that the fields of communications and cryptography are quite distinct and while communications systems often combine technologies from the two fields, a layered architecture is applied that requires no knowledge of the layers above. We discuss how this layered approach can be applied to watermarking applications.

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Gwenael Doerr

Papers

A guide tour of video watermarking

Applying informed coding and embedding to design a robust high-capacity watermark

Security pitfalls of frame-by-frame approaches to video watermarking

Normalized Energy Density-Based Forensic Detection of Resampled Images

Watermarking is not cryptography