In the field of collusion-resistant traitor tracing, Oosterwijk et al. recently determined the optimal suspicion function for simple decoders. Earlier, Moulin also considered another type of decoder: the generic joint decoder that compares all possible coalitions, and showed that usually the generic joint decoder outperforms the simple decoder. Both Amiri and Tardos, and Meerwald and Furon described constructions that assign suspicion levels to c-tuples, where c is the number of colluders. We investigate a novel idea: the tuple decoder, assigning a suspicion level to tuples of a fixed size. In contrast to earlier work, we use this in a novel accusation algorithm to decide for each distinct user whether or not to accuse him. We expect such a scheme to outperform simple decoders while not being as computationally intensive as the generic joint decoder. In this paper we generalize the optimal suspicion functions to tuples, and describe a family of accusation algorithms in this setting that accuses individual users using this tuple-based information.
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