Analysis of Nonlinear Collusion Attacks on Fingerprinting Systems for Compressed Multimedia

In this paper, we analyze the effect of various collusion attacks on fingerprinting systems for compressed multimedia. We evaluate the effectiveness of the collusion attacks in terms of the probability of detection and accuracy in estimating the host signal. Our analysis shows that applying averaging collusion on copies of moderately compressed content gives a highly accurate estimation of the host, and can effectively remove the embedded fingerprints. Averaging is thus the best choice for an attacker as the probability of detection and the distortion introduced are the lowest.