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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Statistically Secure Extension of Anti-collusion Code Fingerprinting
verfasst von : Jae-Min Seol, Seong-Whan Kim
Erschienen in: Distributed Computing and Internet Technology
Verlag: Springer Berlin Heidelberg
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Fingerprinting schemes use digital watermarks to determine originators of unauthorized/pirated copies. Multiple users may collude and collectively escape identification by creating an average or median of their individually watermarked copies. We present a collusion-resilient code, which improves anti-collusion fingerprinting (AND-ACC) scheme using statistically secure matrix. Our approach improves the robustness for non-linear attacks, and can be scalable for large number of users. We experiment our approach using HVS based watermarking scheme, for standard test images, and the results show better collusion detection performance over average and median collusion attacks.