Optimal sequential fingerprinting: Wald vs. Tardos

TL;DR

This paper compares Wald's sequential probability ratio test and the dynamic Tardos scheme for collusion-resistant fingerprinting, showing both are asymptotically optimal and recommending Wald's approach due to its advantages.

Contribution

It demonstrates the asymptotic optimality of both schemes and provides a comparative analysis, advocating for Wald's scheme in practical applications.

Findings

Both schemes are asymptotically optimal for sequential fingerprinting.

Wald's scheme is generally preferable over the dynamic Tardos scheme.

An optimal sequential group testing method is derived as a side result.

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.