A Digital Fingerprint Coding Based on Turbo Codes.
ABSTRACT Digital fingerprinting is a technique for identifying unauthorized copy and tracing back to its user. The distributor marks each individual copy with a unique fingerprint. A group of colluders having access to multiple copies with different fingerprints may construct a pirate object with a fingerprint that cannot be traced. In this paper, we propose a new collusion- secure fingerprinting code which is composed of outer Turbo codes and inner codes based on Boneh-Shaw model. The collusion security, code length and performance are proved and analyzed. The results indicate that the proposed scheme has shorter code length and achieves effective traitor-tracing in large scale contents distribution environments.
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ABSTRACT: . Watermarking techniques allow the tracing of pirated copies of data by modifying each copy as it is distributed, embedding hidden information into the data which identifies the owner of that copy. The owner of the original data can then identify the source of a pirated copy by reading out the hidden information present in that copy. Naturally, one would like these schemes to be as efficient as possible. Previous analyses measured efficiency in terms of the amount of data needed to allow many different copies to be distributed; in order to hide enough data to distinguish many users, the total original data must be sufficiently large. Here, we consider a different notion of efficiency: What resources does the watermark detector need in order to perform this tracing? We address this question in two ways. First, we present a modified version of the CKLS media watermarking algorithm which improves the detector running time from linear to polylogarithmic in the number of users...07/2000;
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ABSTRACT: Digital fingerprinting is a method for protecting digital data in which fingerprints that are embedded in multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion, where several users combine their copies of the same content to attenuate/remove the original fingerprints. In this paper, we study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We introduce the maximum detector and the thresholding detector for colluder identification. We then analyze the collusion resistance of a system to the averaging collusion attack for the performance criteria represented by the probability of a false negative and the probability of a false positive. Lower and upper bounds for the maximum number of colluders K(max) are derived. We then show that the detectors are robust to different collusion attacks. We further study different sets of performance criteria, and our results indicate that attacks based on a few dozen independent copies can confound such a fingerprinting system. We also propose a likelihood-based approach to estimate the number of colluders. Finally, we demonstrate the performance for detecting colluders through experiments using real images.IEEE Transactions on Image Processing 07/2005; 14(6):804-21. · 3.20 Impact Factor
Conference Proceeding: Decoding “turbo”-codes with the soft output Viterbi algorithm (SOVA)[show abstract] [hide abstract]
ABSTRACT: Iterative decoding of two dimensional systematic convolutional codes has been termed “turbo”-(de)coding. It is shown that the simple soft output viterbi algorithm (SOVA) meets all the requirements for iterative decoding if an a priori term is added. With simple 4 and 16 state codes surprisingly good performance is achieved for the Gaussian and Rayleigh channel with a very small degradation relative to the complicated MAP algorithmInformation Theory, 1994. Proceedings., 1994 IEEE International Symposium on; 08/1994