Watermarking security

International audienceThis chapter deals with applications where watermarking is a security primitive included in a larger system protecting the value of multimedia content. In this context, there might exist dishonest users, in the sequel so-called attackers, willing to read/overwrite hidden messages or simply to remove the watermark signal.The goal of this section is to play the role of the attacker. We analyze means to deduce information about the watermarking technique that will later ease the forgery of attacked copies. This chapter first proposes a topology of the threats in Section 6.1, introducing three different concepts: robustness, worst-case attacks, and security. Previous chapter has already discussed watermark robustness. We focus on worst-case attacks in Section 6.2, on the way to measure watermarking security in Section 6.3, and on the classical tools to break a watermarking scheme in Section 6.4. This tour of watermarking security concludes by a summary of what we know and still do not know about it (Section 6.5) and a review of oracle attacks (Section 6.6). Last, Section 6.7 deals with protocol attacks, a notion which underlines the illusion of security that a watermarking primitive might bring when not properly used in some applications

Towards geometrically robust data-hiding with structured codebooks

In this paper we analyze performance of practical robust data-hiding in channels with geometrical transformations. By applying information-theoretic argument we show that performance of a system designed based on both random coding and random binning principles is bounded by the same maximal achievable rate for the cases when communication channel includes geometrical transformations or not. Targeting to provide theoretic performance limits of practical robust data-hiding we model it using a multiple access channel (MAC) with side information (SI) available at one of encoders and present the bounds on achievable rates of reliable communications to such a protocol. Finally, considering template-based and redundant-based design of geometrically robust data-hiding systems, we perform security analysis of their performance and present results in terms of number of trial efforts the attacker needs to completely remove hidden informatio

Robust Logo Watermarking

Digital image watermarking is used to protect the copyright of digital images. In this thesis, a novel blind logo image watermarking technique for RGB images is proposed. The proposed technique exploits the error correction capabilities of the Human Visual System (HVS). It embeds two different watermarks in the wavelet/multiwavelet domains. The two watermarks are embedded in different sub-bands, are orthogonal, and serve different purposes. One is a high capacity multi-bit watermark used to embed the logo, and the other is a 1-bit watermark which is used for the detection and reversal of geometrical attacks. The two watermarks are both embedded using a spread spectrum approach, based on a pseudo-random noise (PN) sequence and a unique secret key. Robustness against geometric attacks such as Rotation, Scaling, and Translation (RST) is achieved by embedding the 1-bit watermark in the Wavelet Transform Modulus Maxima (WTMM) coefficients of the wavelet transform. Unlike normal wavelet coefficients, WTMM coefficients are shift invariant, and this important property is used to facilitate the detection and reversal of RST attacks. The experimental results show that the proposed watermarking technique has better distortion parameter detection capabilities, and compares favourably against existing techniques in terms of robustness against geometrical attacks such as rotation, scaling, and translation

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Wavelet Domain Watermark Detection and Extraction using the Vector-based Hidden Markov Model

Multimedia data piracy is a growing problem in view of the ease and simplicity provided by the internet in transmitting and receiving such data. A possible solution to preclude unauthorized duplication or distribution of digital data is watermarking. Watermarking is an identifiable piece of information that provides security against multimedia piracy. This thesis is concerned with the investigation of various image watermarking schemes in the wavelet domain using the statistical properties of the wavelet coefficients. The wavelet subband coefficients of natural images have significantly non-Gaussian and heavy-tailed features that are best described by heavy-tailed distributions. Moreover the wavelet coefficients of images have strong inter-scale and inter-orientation dependencies. In view of this, the vector-based hidden Markov model is found to be best suited to characterize the wavelet coefficients. In this thesis, this model is used to develop new digital image watermarking schemes. Additive and multiplicative watermarking schemes in the wavelet domain are developed in order to provide improved detection and extraction of the watermark. Blind watermark detectors using log-likelihood ratio test, and watermark decoders using the maximum likelihood criterion to blindly extract the embedded watermark bits from the observation data are designed. Extensive experiments are conducted throughout this thesis using a number of databases selected from a wide variety of natural images. Simulation results are presented to demonstrate the effectiveness of the proposed image watermarking scheme and their superiority over some of the state-of-the-art techniques. It is shown that in view of the use of the hidden Markov model characterize the distributions of the wavelet coefficients of images, the proposed watermarking algorithms result in higher detection and decoding rates both before and after subjecting the watermarked image to various kinds of attacks