International Association
for Cryptologic Research

Forensic watermarking is the application of digital watermarks

for the purpose of tracing unauthorized redistribution of content.

The most powerful type of attack on watermarks is the

collusion attack, in which multiple users compare their differently

watermarked versions of the same content.

Collusion-resistant codes have been developed against these attacks.

One of the most famous such codes is the Tardos code.

It has the asymptotically optimal property that it can resist c

attackers with a code of length proportional to c^2.

Determining error rates for the Tardos code and its various

extensions and generalizations turns out to be a nontrivial problem.

In recent work we developed an approach called the

Convolution and Series Expansion (CSE) method to accurately compute

false positive accusation probabilities.

In this paper we extend the CSE method in order to make it possible

to compute false negative accusation probabilities as well.