34 research outputs found

    Towards joint decoding of binary Tardos fingerprinting codes

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    The class of joint decoder of probabilistic fingerprinting codes is of utmost importance in theoretical papers to establish the concept of fingerprint capacity. However, no implementation supporting a large user base is known to date. This article presents an iterative decoder which is, as far as we are aware of, the first practical attempt towards joint decoding. The discriminative feature of the scores benefits on one hand from the side-information of previously accused users, and on the other hand, from recently introduced universal linear decoders for compound channels. Neither the code construction nor the decoder make precise assumptions about the collusion (size or strategy). The extension to incorporate soft outputs from the watermarking layer is straightforward. An extensive experimental work benchmarks the very good performance and offers a clear comparison with previous state-of-the-art decoders.Comment: submitted to IEEE Trans. on Information Forensics and Security. - typos corrected, one new plot, references added about ECC based fingerprinting code

    Multimedia Protection using Content and Embedded Fingerprints

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    Improved digital connectivity has made the Internet an important medium for multimedia distribution and consumption in recent years. At the same time, this increased proliferation of multimedia has raised significant challenges in secure multimedia distribution and intellectual property protection. This dissertation examines two complementary aspects of the multimedia protection problem that utilize content fingerprints and embedded collusion-resistant fingerprints. The first aspect considered is the automated identification of multimedia using content fingerprints, which is emerging as an important tool for detecting copyright violations on user generated content websites. A content fingerprint is a compact identifier that captures robust and distinctive properties of multimedia content, which can be used for uniquely identifying the multimedia object. In this dissertation, we describe a modular framework for theoretical modeling and analysis of content fingerprinting techniques. Based on this framework, we analyze the impact of distortions in the features on the corresponding fingerprints and also consider the problem of designing a suitable quantizer for encoding the features in order to improve the identification accuracy. The interaction between the fingerprint designer and a malicious adversary seeking to evade detection is studied under a game-theoretic framework and optimal strategies for both parties are derived. We then focus on analyzing and understanding the matching process at the fingerprint level. Models for fingerprints with different types of correlations are developed and the identification accuracy under each model is examined. Through this analysis we obtain useful guidelines for designing practical systems and also uncover connections to other areas of research. A complementary problem considered in this dissertation concerns tracing the users responsible for unauthorized redistribution of multimedia. Collusion-resistant fingerprints, which are signals that uniquely identify the recipient, are proactively embedded in the multimedia before redistribution and can be used for identifying the malicious users. We study the problem of designing collusion resistant fingerprints for embedding in compressed multimedia. Our study indicates that directly adapting traditional fingerprinting techniques to this new setting of compressed multimedia results in low collusion resistance. To withstand attacks, we propose an anti-collusion dithering technique for embedding fingerprints that significantly improves the collusion resistance compared to traditional fingerprints

    Joint Compression and Digital Watermarking: Information-Theoretic Study and Algorithms Development

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    In digital watermarking, a watermark is embedded into a covertext in such a way that the resulting watermarked signal is robust to certain distortion caused by either standard data processing in a friendly environment or malicious attacks in an unfriendly environment. The watermarked signal can then be used for different purposes ranging from copyright protection, data authentication,fingerprinting, to information hiding. In this thesis, digital watermarking will be investigated from both an information theoretic viewpoint and a numerical computation viewpoint. From the information theoretic viewpoint, we first study a new digital watermarking scenario, in which watermarks and covertexts are generated from a joint memoryless watermark and covertext source. The configuration of this scenario is different from that treated in existing digital watermarking works, where watermarks are assumed independent of covertexts. In the case of public watermarking where the covertext is not accessible to the watermark decoder, a necessary and sufficient condition is determined under which the watermark can be fully recovered with high probability at the end of watermark decoding after the watermarked signal is disturbed by a fixed memoryless attack channel. Moreover, by using similar techniques, a combined source coding and Gel'fand-Pinsker channel coding theorem is established, and an open problem proposed recently by Cox et al is solved. Interestingly, from the sufficient and necessary condition we can show that, in light of the correlation between the watermark and covertext, watermarks still can be fully recovered with high probability even if the entropy of the watermark source is strictly above the standard public watermarking capacity. We then extend the above watermarking scenario to a case of joint compression and watermarking, where the watermark and covertext are correlated, and the watermarked signal has to be further compressed. Given an additional constraint of the compression rate of the watermarked signals, a necessary and sufficient condition is determined again under which the watermark can be fully recovered with high probability at the end of public watermark decoding after the watermarked signal is disturbed by a fixed memoryless attack channel. The above two joint compression and watermarking models are further investigated under a less stringent environment where the reproduced watermark at the end of decoding is allowed to be within certain distortion of the original watermark. Sufficient conditions are determined in both cases, under which the original watermark can be reproduced with distortion less than a given distortion level after the watermarked signal is disturbed by a fixed memoryless attack channel and the covertext is not available to the watermark decoder. Watermarking capacities and joint compression and watermarking rate regions are often characterized and/or presented as optimization problems in information theoretic research. However, it does not mean that they can be calculated easily. In this thesis we first derive closed forms of watermarking capacities of private Laplacian watermarking systems with the magnitude-error distortion measure under a fixed additive Laplacian attack and a fixed arbitrary additive attack, respectively. Then, based on the idea of the Blahut-Arimoto algorithm for computing channel capacities and rate distortion functions, two iterative algorithms are proposed for calculating private watermarking capacities and compression and watermarking rate regions of joint compression and private watermarking systems with finite alphabets. Finally, iterative algorithms are developed for calculating public watermarking capacities and compression and watermarking rate regions of joint compression and public watermarking systems with finite alphabets based on the Blahut-Arimoto algorithm and the Shannon's strategy
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