Optimal Sequential Fingerprinting

Abstract

We study sequential collusion-resistant fingerprinting, where the fingerprinting code is generated in advance but accusations may be made between rounds, and show that in this setting both the dynamic Tardos scheme and schemes building upon Wald's sequential probability ratio test (SPRT) are asymptotically optimal. We further compare these two approaches to sequential fingerprinting, highlighting differences between the two schemes. Based on these differences, we argue that Wald's scheme should in general be preferred over the dynamic Tardos scheme, even though both schemes have their merits. As a side result, we derive an optimal sequential group testing method for the classical model, which can easily be generalized to different group testing models.

Nearest Neighbor Decoding for Tardos Fingerprinting Codes

“…Dynamic settings. For streaming applications [14,22,26,41], decisions on whether to accuse users or not need to be made in realtime as well. As the NNS techniques considered here commonly rely on static data, it is not directly obvious whether the same speedups can be obtained when the data arrives in a streaming fashion.…”

“…In particular, past work has shown that joint decoders achieve superior performance to simple decoders [2,7,11,17,18,21,23,30], but are often considered infeasible due to their high decoding complexity. Moreover, in dynamic settings [22,26] where decisions about the accusation of users need to be made swiftly, an efficient decoding method is even more critical. Techniques that can speed up the decoding procedure may therefore be useful for further improving these schemes in practice.…”