Efficient Probabilistic Group Testing Based on Traitor Tracing

TL;DR

This paper introduces a new probabilistic group testing framework inspired by traitor tracing, achieving near-optimal test efficiency and applicable to various noisy and threshold models.

Contribution

It presents a novel framework for probabilistic group testing based on traitor tracing techniques, improving test efficiency across multiple models.

Findings

Requires approximately 2K ln N tests for K defectives among N items.

Applicable to noisy and threshold group testing models.

Framework works in both adaptive and non-adaptive settings.

Abstract

Inspired by recent results from collusion-resistant traitor tracing, we provide a framework for constructing efficient probabilistic group testing schemes. In the traditional group testing model, our scheme asymptotically requires T ~ 2 K ln N tests to find (with high probability) the correct set of K defectives out of N items. The framework is also applied to several noisy group testing and threshold group testing models, often leading to improvements over previously known results, but we emphasize that this framework can be applied to other variants of the classical model as well, both in adaptive and in non-adaptive settings.