Title :
Colluder Detection for Nonlinear Collusion Attacks
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Chicago, Chicago, IL
fDate :
Oct. 29 2006-Nov. 1 2006
Abstract :
We investigate the problem of colluder identification for digital fingerprinting systems under nonlinear collusion attacks. Formulating colluder detection as a binary hypothesis testing problem, we derive the log-likelihood ratio tests for various nonlinear collusion attacks. Utilizing the approximate distribution of the order statistics, we obtain suboptimal detection statistics with low complexity. Compared with the existing correlation-based detectors, these detectors provide substantial improvement in both detection performance and computational complexity.
Keywords :
fingerprint identification; security of data; colluder detection; colluder identification; computational complexity; correlation-based detectors; digital fingerprinting systems; log-likelihood ratio tests; nonlinear collusion attacks; Computational complexity; Cryptography; Degradation; Detectors; Fingerprint recognition; Statistical distributions; Statistics; Technology management; Testing; Watermarking;
Conference_Titel :
Signals, Systems and Computers, 2006. ACSSC '06. Fortieth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
1-4244-0784-2
Electronic_ISBN :
1058-6393
DOI :
10.1109/ACSSC.2006.354819
