Digital watermarking, information embedding, and data hiding systems

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 139-142).Digital watermarking, information embedding, and data hiding systems embed information, sometimes called a digital watermark, inside a host signal, which is typically an image, audio signal, or video signal. The host signal is not degraded unacceptably in the process, and one can recover the watermark even if the composite host and watermark signal undergo a variety of corruptions and attacks as long as these corruptions do not unacceptably degrade the host signal. These systems play an important role in meeting at least three major challenges that result from the widespread use of digital communication networks to disseminate multimedia content: (1) the relative ease with which one can generate perfect copies of digital signals creates a need for copyright protection mechanisms, (2) the relative ease with which one can alter digital signals creates a need for authentication and tamper-detection methods, and (3) the increase in sheer volume of transmitted data creates a demand for bandwidth-efficient methods to either backwards-compatibly increase capacities of existing legacy networks or deploy new networks backwards-compatibly with legacy networks. We introduce a framework within which to design and analyze digital watermarking and information embedding systems. In this framework performance is characterized by achievable rate-distortion-robustness trade-offs, and this framework leads quite naturally to a new class of embedding methods called quantization index modulation (QIM). These QIM methods, especially when combined with postprocessing called distortion compensation, achieve provably better rate-distortion-robustness performance than previously proposed classes of methods such as spread spectrum methods and generalized low-bit modulation methods in a number of different scenarios, which include both intentional and unintentional attacks. Indeed, we show that distortion-compensated QIM methods can achieve capacity, the information-theoretically best possible rate-distortion-robustness performance, against both additive Gaussian noise attacks and arbitrary squared error distortion-constrained attacks. These results also have implications for the problem of communicating over broadcast channels. We also present practical implementations of QIM methods called dither modulation and demonstrate their performance both analytically and through empirical simulations.by Brian Chen.Ph.D

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