Optimal sequential fingerprinting: Wald vs. Tardos
This work addresses fingerprinting for digital content protection, offering incremental improvements in sequential accusation methods.
The paper tackled sequential collusion-resistant fingerprinting by showing that both dynamic Tardos and Wald's SPRT-based schemes are asymptotically optimal, and argued that Wald's scheme is generally preferable despite both having merits.
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.