Abstract

Video streaming, or the real-time delivery of video over a data network, is the underlying technology behind many applications including video conferencing, video-on-demand, and the delivery of educational and entertainment content. In many applications, particularly ones involving entertainment content, security issues, such as conditional access and copy protection must be addressed. To resolve these security issues, techniques that include encryption and watermarking need to be developed. Since the video sequences will often be compressed using a scalable compression technique and transported over a lossy packet network using the Internet Protocol (IP), the security techniques must be compatible with the compression method and data transport and be robust to errors. In this paper, we address the issues involved in the watermarking of rate-scalable video streams delivered using a practical network. Watermarking is the embedding of a signal (the watermark) into a video stream that is imperceptible when the stream is viewed but can be detected by a watermark detector. Many watermarking techniques have been proposed for digital images and video, but the issues of streaming have not been fully investigated. A review of streaming video is presented, including scalable video compression and network transport, followed by a brief review of video watermarking and the discussion of watermarking streaming video.

We discuss in this paper the issues related to image watermarking benchmarking and scenarios based on digital rights management requirements. We show that improvements are needed in image quality evaluation, specially related to image geometrical deformation assessments, in risk evaluation related to specific delivery scenarios and in multidimensional criteria evaluation. Efficient benchmarking is still an open issue and we suggest the use of open-source Web-based evaluation systems for the collective progresses in this domain.

creators; however, the ability for anyone to make perfect copies and the ease by which those copies can be distributed also facilitate misuse, illegal copying and distribution (

Tables of factorizations of the numbers in the title, and a description of how they were factored.  Numbers of this form appear often in problems in number theory and cryptography.

While Digital Watermarking has received much attention within the academic community and private sector in recent years, it is still a relatively young technology. As such, there are few accepted tools and metrics that can be used to validate the performance claims asserted by members of the research community and evaluate the suitability of a watermarking technique for specific applications. This lack of a universally adopted set of metrics and methods has motivated us to develop a web-based digital watermark evaluation system known as the Watermark Evaluation Testbed or WET. This system has undergone several improvements since its inception. The ultimate goal of this work has been to develop a platform, where any watermarking researcher can test not only the performance of known techniques, but also their own techniques. This goal has been reached by the latest version of the system. New tools and concepts have been designed to achieve the desired objectives. This paper describes the new features of WET. Moreover, we also summarize the development process of the entire project as well as introduce new directions for future work.

Robust watermarks are evaluated in terms of image fidelity and robustness. We extend this framework and apply reliability testing to robust watermark evaluation. Reliability is the probability that a watermarking algorithm will correctly detect or decode a watermark for a specified fidelity requirement under a given set of attacks and images. In reliability testing, a system is evaluated in terms of quality, load, capacity and performance. To measure quality that corresponds to image fidelity, we compensate for attacks to measure the fidelity of attacked watermarked images. We use the conditional mean of pixel values to compensate for valumetric attacks such as gamma correction and histogram equalization. To compensate for geometrical attacks, we use error concealment and perfect motion estimation assumption. We define capacity to be the maximum embedding strength parameter and the maximum data payload. Load is then defined to be the actual embedding strength and data payload of a watermark. To measure performance, we use bit error rate (BER) and receiver operating characteristics (ROC) and area under the curve (AUC) of the ROC curve of a watermarking algorithm for different attacks and images. We evaluate robust watermarks for various quality, loads, attacks, and images.

The growth of networked multimedia systems has magnified the need for image copyright protection. One approach used to address this problem is to add an invisible structure to an image that can be used to seal or mark it. These structures are known as digital watermarks. In this paper we describe two techniques for the invisible marking of images. We analyze the robustness of the watermarks with respect to linear and nonlinear filtering, and JPEG compression. The results show that our watermarks detect all but the most minute changes to the image.

The growth of networked multimedia systems has created a need for the copyright protection of digital images. Copyright protection involves the authentication of image ownership and the identification of illegal copies of a (possibly forged) image. One approach is to mark an image by adding an invisible structure known as a digital watermark. In this paper we further study techniques for marking images introduced in [1]. In particular, we describe how our techniques withstand random errors. We also provide more details relative to our verification procedure. Finally, we discuss the recently proposed IBM attack.

The growth of networked multimedia systems has complicated copyright enforcement relative to digital images. One way to protect the copyright of digital images is to add an invisible structure to the image (known as a digital watermark) to identify the owner. In particular, it is important for Internet and image database applications that as much of the watermark as possible remain in the image after compression. Image adaptive watermarks are particularly resistant to removal by signal processing attacks such as filtering or compression. Common image adaptive watermarks operate in the transform domain (DCT or wavelet); the same domains are also used for popular image compression techniques (JPEG, EZW). This paper investigates whether matching the watermarking domain to the compression transform domain will make the watermark more robust to compression.

Two classes of digital watermarks have been developed to protect the copyright ownership of digital images. Robust watermarks are designed to withstand attacks on an image (such as compression or scaling), while fragile watermarks are designed to detect minute changes in an image. Fragile marks can also identify where an image has been altered. This paper compares two fragile watermarks. The first method uses a hash function to obtain a digest of the image. An altered or forged version of the original image is then hashed and the digest is compared to the digest of the original image. If the image has changed the digests will be different. We will describe how images can be hashed so that any changes can be spatially localized. The second method uses the Variable-Watermark Two-Dimensional algorithm (VW2D) [1]. The sensitivity to changes is user-specific. Either no changes can be permitted (similar to a hard hash function), or an image can be altered and still be labeled authentic. Latter algorithms are known as semi-fragile watermarks. We will describe the performance of these two techniques and discuss under what circumstances one would use a particular technique.

The growth of new imaging technologies has created a need for techniques that can be used for copyright protection of digital images. Copyright protection involves the authentication of image content and/or ownership and can be used to identify illegal copies of a (possibly forged) image. One approach for copyright protection is to introduce an invisible signal known as a digital watermark in the image. In this paper, we describe digital image watermarking techniques, known as perceptually based watermarks, that are designed to exploit aspects of the human visual system. In the most general sense, any watermarking technique that attempts to incorporate an invisible mark into an image is perceptually based. However, in order to provide transparency (invisibility of the watermark) and robustness to attack, more sophisticated use of perceptual information in the watermarking process is required. Several techniques have been introduced that incorporate a simple visual model in the marking procedure. Such techniques usually take advantage of frequency selectivity and weighing to provide some perceptual criteria in the watermarking process. Even more elaborate visual models are used to develop schemes that not only take advantage of frequency characteristics but also adapt to the local image characteristics, providing extremely robust as well as transparent schemes. We present examples from each category - from the simple schemes that guarantee transparency to the more elaborate schemes that use visual models to provide robustness as well as transparency.

We describe a blind watermarking technique for digital images. Our technique constructs an image-dependent watermark in the discrete wavelet transform (DWT) domain and inserts the watermark in the most signifcant coefficients of the image. The watermarked coefficients are determined by using the hierarchical tree structure induced by the DWT, similar in concept to embedded zerotree wavelet (EZW) compression. If the watermarked image is attacked or manipulated such that the set of significant coefficients is changed, the tree structure allows the correlation-based watermark detector to recover synchronization.Our technique also uses a visual adaptive scheme to insert the watermark to minimize watermark perceptibility. The visual adaptive scheme also takes advantage of the tree structure. Finally, a template is inserted into the watermark to provide robustness against geometric attacks. The template detection uses the cross-ratio of four collinear points.

While Digital Watermarking has received much attention in recentyears, it is still a relatively young technology. There are fewaccepted tools/metrics that can be used to evaluate the suitabilityof a watermarking technique for a specific application. This lack ofa universally adopted set of metrics/methods has motivated us todevelop a web-based digital watermark evaluation system called theWatermark Evaluation Testbed or WET. There have beenmore improvements over the first version of WET. Weimplemented batch mode with a queue that allows for user submittedjobs. In addition to StirMark 3.1 as an attack module, we addedattack modules based on StirMark 4.0. For a new image fidelitymeasure, we evaluate conditional entropy as an image fidelitymeasure for different watermarking algorithms and different attacks.Also, we show the results of curve fitting the Receiver OperatingCharacteristic (ROC) analysis data using the Parzen window densityestimation. The curve fits the data closely while having only twoparameters to estimate.