This paper presents a new stochastic approach which can be applied with di erent w atermark techniques. The approach is based on the computation of a Noise Visibility F unction NVF that characterizes the local image properties, identifying textured and edge regions where the mark should be more strongly embedded. We present precise formulas for the NVF which enable a fast computation during the watermark encoding and decoding process. In order to determine the optimal NVF, we rst consider the watermark as noise. Using a classical MAP image denoising approach, we show h o w to estimate the "noise". This leads to a general formulation for a texture masking function, that allows us to determine the optimal watermark locations and strength for the watermark embedding stage. We examine two such NVFs, based on either a non-stationary Gaussian model of the image, or a stationary Generalized Gaussian model. We show that the problem of the watermark estimation is equivalent to image denoising and derive content adaptive criteria. Results show that watermark visibility is noticeably decreased, while at the same time enhancing the energy of the watermark.

Research in digital watermarking has progressed along two paths. While new watermarking technologies are being developed, some researchers are also investigating different ways of attacking digital watermarks. Common attacks to waterrnarks usually aim to destroy the embedded watermark or to impair its detection. In this paper we propose a conceptually new attack for digitally watermarked images. The proposed attack does not destroy an embedded watermark, but copies it from one image to a different image. Although this new attack does not destroy a watermark or impair its detection, it creates new challenges, especially when watermarks are used for copyright protection and identification. The process of copying the watermark requires neither algorithmic knowledge of the watermarking technology nor the watermarking key. The attack is based on an estimation of the embedded watermark in the spatial domain through a filtering process. The estimate of the watermark is then adapted and inserted into the target image. To illustrate the performance of the proposed attack we applied it to commercial and non-commercial watermarking schemes. The experiments showed that the attack is very effective in copying a watermark from one image to a different image. In addition, we have a closer look at application dependent implications of this new attack.

Digital image watermarking has become a popular technique for authentication and copyright protection. For verifying the security and robustness of watermarking algorithms, specific attacks have to be applied to test them. In contrast to the known Stirmark attack, which degrades the quality of the image while destroying the watermark, this paper presents a new approach which is based on the estimation of a watermark and the exploitation of the properties of Human Visual System (HVS). The new attack satisfies two important requirements. First, image quality after the attack as perceived by the HVS is not worse than the quality of the stego image. Secondly, the attack uses all available prior information about the watermark and cover image statistics to perform the best watermark removal or damage. The proposed attack is based on a stochastic formulation of the watermark removal problem, considering the embedded watermark as additive noise with some probability distribution. The attack scheme consists of two main stages: a) watermark estimation and partial removal by a filtering based on a Maximum a Posteriori (MAP) approach; b) watermark alteration and hiding through addition of noise to the filtered image, taking into account the statistics of the embedded watermark and exploiting HVS characteristics. Experiments on a number of real world and computer generated images show the high efficiency of the proposed attack against known academic and commercial methods: the watermark is completely destroyed in all tested images without altering the image quality. The approach can be used against watermark embedding schemes that operate either in coordinate domain, or transform domains like Fourier, DCT or wavelet.

Abstract. This paper2 presents a new approach for the secure and robust copyright protection of digital images. A system for generating digital watermarks and for trading watermarked images is described. The system is based on a new watermarking technique, which is robust against image transformation techniques such as compression, rotation, translation, scaling and cropping. It uses modulation of the magnitude components in Fourier space to embed a watermark and an accompanying template and, during watermark extraction, reads a template in the log polar transform of the frequency domain. The template is used for analyzing scaling and rotation suffered by the watermarked stego-image. The detection of the watermarks is also possible without any need for the original cover-image. In addition, the system applies asymmetric cryptographic protocols for different purposes, namely embedding/detecting the watermark and transferring watermarked data. The public key technique is applied for the construction of a one-way watermark embedding and the verification function to identify and prove the uniqueness of the watermark. Legal dispute resolution is supported for the multiple watermarking of a digital image without revealing the confidential keying information.

This paper presents a new attack, called the watermark template attack, for watermarked images. In contrast to the Stirmark benchmark [1-2], this attack does not severely reduce the quality of the image. This attack maintains, therefore, the commercial value of the watermarked image. In contrast to previous approaches [3-4], it is not the aim of the attack to change the statistics of embedded watermarks fooling the detection process but to utilize specific concepts that have been recently developed for more robust watermarking schemes. The attack estimates the corresponding template points in the FFT domain and then removes them using local interpolation. We demonstrate the effectiveness of the attack showing different test cases that have been watermarked with commercial available watermark products. The approach presented is not limited to the FFT domain. Other transformation domains may be also exploited by very similar variants of the described attack.