@article {18168,
title = {Anti-collusion forensics of multimedia fingerprinting using orthogonal modulation},
journal = {Image Processing, IEEE Transactions on},
volume = {14},
year = {2005},
month = {2005/06//},
pages = {804 - 821},
abstract = {Digital fingerprinting is a method for protecting digital data in which fingerprints that are embedded in multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion, where several users combine their copies of the same content to attenuate/remove the original fingerprints. In this paper, we study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We introduce the maximum detector and the thresholding detector for colluder identification. We then analyze the collusion resistance of a system to the averaging collusion attack for the performance criteria represented by the probability of a false negative and the probability of a false positive. Lower and upper bounds for the maximum number of colluders K_{max} are derived. We then show that the detectors are robust to different collusion attacks. We further study different sets of performance criteria, and our results indicate that attacks based on a few dozen independent copies can confound such a fingerprinting system. We also propose a likelihood-based approach to estimate the number of colluders. Finally, we demonstrate the performance for detecting colluders through experiments using real images.},
keywords = {Automated;Product Labeling;Signal Processing, Computer-Assisted;, Computer-Assisted;Multimedia;Patents as Topic;Pattern Recognition, Gaussian distribution;anticollusion forensic;colluder identification;collusion resistance;digital fingerprinting;false probability;likelihood-based approach;multimedia fingerprinting;orthogonal modulation;spread spectrum embedding;Gaussian distribution;fi},
isbn = {1057-7149},
doi = {10.1109/TIP.2005.847284},
author = {Wang,Z.J. and M. Wu and Zhao,H.V. and Trappe,W. and Liu,K. J.R}
}