00000cab a22000003a 4500 UP-99796217608882258 Buklod 20231007234001.0 m |o d | ta 090619s xx d | ||r ||||| || DENGII eng Voloshynovskiy, S. Attacks on digital watermarks classification, estimation basedattacks, and benchmarks. pp. 118-126 Watermarking is a potential method for protection of ownership rights on digital audio, image, and video data. Benchmarks are used to evaluate the performance of different watermarking algorithms. For image watermarking, the Stirmark package is the most popular benchmark, and the best current algorithms perform well against it. However, results obtained by the Stirmark benchmark have to be handled carefully since Stirmark does not properly model the watermarking process and consequently is limited in its potential for impairing sophisticated image watermarking schemes. In this context, the goal of this article is threefold. First, we give an overview of the current attacking methods. Second, we describe attacks exploiting knowledge about the statistics of the original data and the embedded watermark. We propose a stochastic formulation of estimation-based attacks. Such attacks consist of two main stages: watermark estimation, exploitation of the estimated watermark to trick watermark detection or create ownership ambiguity. The full strength of estimation-based attacks can be achieved by introducing additional noise, where the attacker tries to combine the estimated watermark and the additive noise to impair watermark communication as much as possible while fulfilling a quality constraint on the attacked data. With a sophisticated quality constraint it is also possible to exploit human perception: the human auditory system in case of audio watermarks and the human visual system in case of image and video watermarks. Third, we discuss the current status of image watermarking benchmarks. We present Petitcolas'(see Electronic Imaging '99: Security and Watermarking of Multimedia Content, SPIE Proc., vol.3657, San Jose, CA, 1999) Stirmark benchmarking tool. Next, we consider the benchmark proposed by the University of Geneva Vision Group that contains more deliberate attacks. Finally, we summarize the current work of the European Certimark project, whose goal is to accelerate efforts from a number of research groups and companies in order to produce an improved ensemble of benchmarking tools European Certimark project. Stirmark package. University of Geneva. Additive noise. Attacked data. Attacking methods. Audio watermarks. Benchmarking tools. Classification. Data statistics. Digital audio. Digital watermarks. Embedded watermark. Estimated watermark. Estimation based attacks. Human auditory system. Human perception. Image watermarking benchmarks. Ownership ambiguity. Ownership rights protection. Performance evaluation. Quality constraint. Stochastic formulation. Video data. Video watermarks. Watermark communication. Watermark detection. Watermark estimation. Watermarking algorithms. IEEE Communications magazine 39, 8 (2001). FO UPD DENG-II Article