ACM Transactions on Mathematical Software (TOMS)
Optimal probabilistic fingerprint codes
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
The Art of Computer Programming, Volume 4, Fascicle 3: Generating All Combinations and Partitions
The Art of Computer Programming, Volume 4, Fascicle 3: Generating All Combinations and Partitions
Symmetric Tardos fingerprinting codes for arbitrary alphabet sizes
Designs, Codes and Cryptography
High rate fingerprinting codes and the fingerprinting capacity
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
An improvement of discrete Tardos fingerprinting codes
Designs, Codes and Cryptography
Experimental assessment of the reliability for watermarking and fingerprinting schemes
EURASIP Journal on Information Security
Linear universal decoding for compound channels
IEEE Transactions on Information Theory
Short collusion-secure fingerprint codes against three pirates
IH'10 Proceedings of the 12th international conference on Information hiding
Asymptotic fingerprinting capacity in the combined digit model
IH'12 Proceedings of the 14th international conference on Information Hiding
Optimal suspicion functions for tardos traitor tracing schemes
Proceedings of the first ACM workshop on Information hiding and multimedia security
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'Don Quixote' is a new accusation process for Tardos traitor tracing codes which is, as far as we know, the first practical implementation of joint decoding. The first key idea is to iteratively prune the list of potential colluders to keep the computational effort tractable while going from single, to pair,... to t-subset joint decoding. At the same time, we include users accused in previous iterations as side-information to build a more discriminative test. The second idea, coming from the field of mismatched decoders and compound channels, is to use a linear decoder based on the worst case perceived collusion channel. The decoder is tested under two accusation policies: to catch one colluder, or to catch as many colluders as possible. The probability of false positive is controlled thanks to a rare event estimator. We describe a fast implementation supporting millions of users and compare our results with two recent fingerprinting codes.