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Abstract: We study blind fingerprinting, where the host sequence into whichfingerprints are embedded is partially or completely unknown to the decoder.This problem relates to a multiuser version of the Gel-fand-Pinsker problem.The number of colluders and the collusion channel are unknown, and thecolluders and the fingerprint embedder are subject to distortion constraints.We propose a conditionally constant-composition random binning scheme and auniversal decoding rule and derive the corresponding false-positive andfalse-negative error exponents. The encoder is a stacked binning scheme andmakes use of an auxiliary random sequence. The decoder is a {\em maximumdoubly-penalized mutual information decoder}, where the significance of eachcandidate coalition is assessed relative to a threshold that trades offfalse-positive and false-negative error exponents. The penalty is proportionalto coalition size and is a function of the conditional type of host sequence.Positive exponents are obtained at all rates below a certain value, which istherefore a lower bound on public fingerprinting capacity. We conjecture thatthis value is the public fingerprinting capacity. A simpler threshold decoderis also given, which has similar universality properties but also lowerachievable rates. An upper bound on public fingerprinting capacity is alsoderived.

Autor: Ying Wang, Pierre Moulin


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