Information theoretic analysis of watermarking systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 185-193).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Watermarking models a copyright protection mechanism where an original data sequence is modified before distribution to the public in order to embed some extra information. The embedding should be transparent (i.e., the modified data should be similar to the original data) and robust (i.e., the information should be recoverable even if the data is modified further). In this thesis, we describe the information-theoretic capacity of such a system as a function of the statistics of the data to be watermarked and the desired level of transparency and robustness. That is, we view watermarking from a communication perspective and describe the maximum bit-rate that can be reliably transmitted from encoder to decoder. We make the conservative assumption that there is a malicious attacker who knows how the watermarking system works and who attempts to design a forgery that is similar to the original data but that does not contain the watermark. Conversely, the watermarking system must meet its performance criteria for any feasible attacker and would like to force the attacker to effectively destroy the data in order to remove the watermark. Watermarking can thus be viewed as a dynamic game between these two players who are trying to minimize and maximize, respectively, the amount of information that can be reliably embedded. We compute the capacity for several scenarios, focusing largely on Gaussian data and a squared difference similarity measure.(cont.) In contrast to many suggested watermarking techniques that view the original data as interference, we find that the capacity increases with the uncertainty in the original data. Indeed, we find that out of all distributions with the same variance, a Gaussian distribution on the original data results in the highest capacity. Furthermore, for Gaussian data, the capacity increases with its variance. One surprising result is that with Gaussian data the capacity does not increase if the original data can be used to decode the watermark. This is reminiscent of a similar model, Costa's "writing on dirty paper", in which the attacker simply adds independent Gaussian noise. Unlike with a more sophisticated attacker, we show that the capacity does not change for Costa's model if the original data is not Gaussian.by Aaron Seth Cohen.Ph.D

On the data hiding theory and multimedia content security applications

This dissertation is a comprehensive study of digital steganography for multimedia content protection. With the increasing development of Internet technology, protection and enforcement of multimedia property rights has become a great concern to multimedia authors and distributors. Watermarking technologies provide a possible solution for this problem. The dissertation first briefly introduces the current watermarking schemes, including their applications in video,, image and audio. Most available embedding schemes are based on direct Spread Sequence (SS) modulation. A small value pseudo random signature sequence is embedded into the host signal and the information is extracted via correlation. The correlation detection problem is discussed at the beginning. It is concluded that the correlator is not optimum in oblivious detection. The Maximum Likelihood detector is derived and some feasible suboptimal detectors are also analyzed. Through the calculation of extraction Bit Error Rate (BER), it is revealed that the SS scheme is not very efficient due to its poor host noise suppression. The watermark domain selection problem is addressed subsequently. Some implications on hiding capacity and reliability are also studied. The last topic in SS modulation scheme is the sequence selection. The relationship between sequence bandwidth and synchronization requirement is detailed in the work. It is demonstrated that the white sequence commonly used in watermarking may not really boost watermark security. To address the host noise suppression problem, the hidden communication is modeled as a general hypothesis testing problem and a set partitioning scheme is proposed. Simulation studies and mathematical analysis confirm that it outperforms the SS schemes in host noise suppression. The proposed scheme demonstrates improvement over the existing embedding schemes. Data hiding in audio signals are explored next. The audio data hiding is believed a more challenging task due to the human sensitivity to audio artifacts and advanced feature of current compression techniques. The human psychoacoustic model and human music understanding are also covered in the work. Then as a typical audio perceptual compression scheme, the popular MP3 compression is visited in some length. Several schemes, amplitude modulation, phase modulation and noise substitution are presented together with some experimental results. As a case study, a music bitstream encryption scheme is proposed. In all these applications, human psychoacoustic model plays a very important role. A more advanced audio analysis model is introduced to reveal implications on music understanding. In the last part, conclusions and future research are presented

Oblivious data hiding : a practical approach

This dissertation presents an in-depth study of oblivious data hiding with the emphasis on quantization based schemes. Three main issues are specifically addressed: 1. Theoretical and practical aspects of embedder-detector design. 2. Performance evaluation, and analysis of performance vs. complexity tradeoffs. 3. Some application specific implementations. A communications framework based on channel adaptive encoding and channel independent decoding is proposed and interpreted in terms of oblivious data hiding problem. The duality between the suggested encoding-decoding scheme and practical embedding-detection schemes are examined. With this perspective, a formal treatment of the processing employed in quantization based hiding methods is presented. In accordance with these results, the key aspects of embedder-detector design problem for practical methods are laid out, and various embedding-detection schemes are compared in terms of probability of error, normalized correlation, and hiding rate performance merits assuming AWGN attack scenarios and using mean squared error distortion measure. The performance-complexity tradeoffs available for large and small embedding signal size (availability of high bandwidth and limitation of low bandwidth) cases are examined and some novel insights are offered. A new codeword generation scheme is proposed to enhance the performance of low-bandwidth applications. Embeddingdetection schemes are devised for watermarking application of data hiding, where robustness against the attacks is the main concern rather than the hiding rate or payload. In particular, cropping-resampling and lossy compression types of noninvertible attacks are considered in this dissertation work

Digital Watermarking, Fingerprinting and Compression: An Information-Theoretic Perspective

The ease with which digital data can be duplicated and distributed over the media and the Internethas raised many concerns about copyright infringement.In many situations, multimedia data (e.g., images, music, movies, etc) are illegally circulated, thus violatingintellectual property rights. In an attempt toovercome this problem, watermarking has been suggestedin the literature as the most effective means for copyright protection and authentication. Watermarking is the procedure whereby information (pertaining to owner and/or copyright) is embedded into host data, such that it is:(i) hidden, i.e., not perceptually visible; and(ii) recoverable, even after a (possibly malicious) degradation of the protected work. In this thesis,we prove some theoretical results that establish the fundamental limits of a general class of watermarking schemes. The main focus of this thesis is the problem ofjoint watermarking and compression of images, whichcan be briefly described as follows: due to bandwidth or storage constraints, a watermarked image is distributed in quantized form, using $R_Q$ bits per image dimension, and is subject to some additional degradation (possibly due to malicious attacks). The hidden message carries $R_W$ bits per image dimension. Our main result is the determination of the region of allowable rates $(R_Q, R_W)$, such that: (i) an average distortion constraint between the original and the watermarked/compressed image is satisfied, and (ii) the hidden message is detected from the degraded image with very high probability. Using notions from information theory, we prove coding theorems that establish the rate regionin the following cases: (a) general i.i.d. image distributions,distortion constraints and memoryless attacks, (b) memoryless attacks combined with collusion (for fingerprinting applications), and (c) general---not necessarily stationary or ergodic---Gaussian image distributions and attacks, and average quadratic distortion constraints. Moreover, we prove a multi-user version of a result by Costa on the capacity of a Gaussian channel with known interference at the encoder