Abstract—An information-theoretic analysis of information hiding is presented in this paper, forming the theoretical basis for design of information-hiding systems. Information hiding is an emerging research area which encompasses applications such as copyright protection for digital media, watermarking, fingerprinting, steganography, and data embedding. In these applications, information is hidden within a host data set and is to be reliably communicated to a receiver. The host data set is intentionally corrupted, but in a covert way, designed to be imperceptible to a casual analysis. Next, an attacker may seek to destroy this hidden information, and for this purpose, introduce additional distortion to the data set. Side information (in the form of cryptographic keys and/or information about the host signal) may be available to the information hider and to the decoder. We formalize these notions and evaluate the hiding capacity, which upper-bounds the rates of reliable transmission and quantifies the fundamental tradeoff between three quantities: the achievable information-hiding rates and the allowed distortion levels for the information hider and the attacker. The hiding capacity is the value of a game between the information hider and the attacker. The optimal attack strategy is the solution of a particular rate-distortion problem, and the optimal hiding strategy is the solution to a channel-coding problem. The hiding capacity is derived by extending the Gel’fand–Pinsker theory of communication with side information at the encoder. The extensions include the presence of distortion constraints, side information at the decoder, and unknown communication channel. Explicit formulas for capacity are given in several cases, including Bernoulli and Gaussian problems, as well as the important special case of small distortions. In some cases, including the last two above, the hiding capacity is the same whether or not the decoder knows the host data set. It is shown that many existing information-hiding systems in the literature operate far below capacity. Index Terms—Channel capacity, cryptography, fingerprinting, game theory, information hiding, network information theory,

Using a theoretical approach based on random processes, signal processing, and information theory, we study the performance of digital watermarks subjected to an attack consisting of linear shift-invariant filtering and additive colored Gaussian noise. Watermarking is viewed as communication over a hostile channel, where the attack takes place. The attacker attempts to minimize the channel capacity under a constraint on the attack distortion (distortion of the attacked signal), and the owner attempts to maximize the capacity under a constraint on the embedding distortion (distortion of the watermarked signal). The distortion measure is frequency-weighted mean-squared error (MSE). In a conventional additive-noise channel, communication is most difficult when the noise is white and Gaussian, so we first investigate an effective white-noise attack based on this principle. We then consider the problem of resisting this attack and show that capacity is maximized when a power-spectrum condition (PSC) is fulfilled. The PSC states that the power spectrum of the watermark should be directly proportional to that of the original signal. However, unlike a conventional channel, the hostile attack channel adapts to the watermark, not vice versa. Hence, the effective white-noise attack is suboptimal. We derive the optimum attack, which minimizes the channel capacity for a given attack distortion. The attack can be roughly characterized by a rule-of-thumb: At low attack distortions, it adds noise, and at high attack distortions, it discards frequency components. Against the optimum attack, the PSC does not maximize capacity at all attack distortions. Also, there is no unique watermark power spectrum that maximizes capacity over the entire range of attack distortions. T...

Inspired by a recently proposed constructive framework for the distributed source coding problem, 1 we propose a powerful constructive approach to the watermarking problem, emphasizing the dual roles of "source codes" and "channel codes." In our framework, we explore various source and channel codes to achieve watermarks that are robust to attackers in terms of maximizing the distortion between the corrupted coded-source signal and the original signal while holding the distortion between the coded-source signal and the original signal constant. We solve the resulting combinatorial optimization problem using an original technique based on robust optimization and convex programming. Keywords: Data Hiding, Digital Watermarking, Multimedia, Convex Optimization, Robustness 1. INTRODUCTION Digital watermarking (data hiding) is an emerging research area that has received a considerable amount of attention in recent years. The basic idea behind digital watermarking is to embed information...

In a variety of applications, there is a need to authenticate a source that may have been degraded, transformed, edited, or otherwise modified, either intentionally or unintentionally. We develop a formulation of this problem, and identify and interpret the associated informationtheoretic performance limits. The results are illustrated through application to binary sources with Hamming distortion measures, and to Gaussian sources with quadratic distortion measures.

Inspired by a recently proposedconstructive framework for the distributed source coding problem [1], we propose a powerful constructive approach to the watermarking problem, emphasizing the dual roles of distributed source coding with side information at the decoder and channel coding with side information at the encoder. In our framework, we explore various source and channel codes to close the gap on the achievable capacity of watermarking systems [2]. We propose two methods of solution, one which is based on optimal rate-distortion quantizers and the other basedon robust optimization and convex programming. The resulting watermarking schemes,when subjectedto additive white gaussiannoise (AWGN) attacks, achieve results which are comparable to or better than the best watermarking schemes in the literature. 1. INTRODUCTION Digital watermarking (data hiding) is an emerging research area that has received a considerable amount of attention in recent years. The basic idea behind digital...

this paper is devoted to extracting some of its implications.