On the Design and Optimization of Tardos Probabilistic Fingerprinting Codes

Abstract

G. Tardos [1] was the first to give a construction of a fingerprinting code whose length meets the lowest known bound in $O(c^{2}\log\frac{n}{\epsilon_{1}})$. This was a real breakthrough because the construction is very simple. Its efficiency comes from its probabilistic nature. However, although G. Tardos almost gave no argument of his rationale, many parameters of his code are precisely fine-tuned. This paper proposes this missing rationale supporting the code construction. The key idea is to render the statistics of the scores as independent as possible from the collusion process. Tardos optimal parameters are rediscovered. This interpretation allows small improvements when some assumptions hold on the collusion process.