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Proceedings Paper

Application of WBE sequence sets to collusion-resistant fingerprinting
Author(s): Zang Li; Wade K. Trappe
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Paper Abstract

Digital fingerprinting has been widely used to protect multimedia content from being used for unauthorized purposes. Digital fingerprints are often embedded in the host media signal using watermarking techniques that are known to be resistant to a variety of processing attacks. However, one cost-effective strategy to attack digital fingerprints is collusion, where several colluders average their individual copies to disrupt the underlying fingerprints. Recently, a new class of fingerprinting codes, called anti-collusion codes (ACC), has been proposed for use with code-modulated data embedding. In designing digital fingerprints that are resistant to collusion attacks, there are several important design considerations: how can we accommodate as many users as possible for a given fingerprint dimensionality, and how can we identify the colluders effectively from the colluded signal? In this work, we identify an underlying similarity between the colluder detection problem and the multiuser detection problem from code division multiple access (CDMA). We propose that fingerprints can be constructed using sequence sets satisfying the Welch Bound Equality (WBE). WBE sequences have been shown to be optimal in synchronous CDMA. In order to identify the colluders when employing WBE-based ACC, we further propose a detection algorithm utilizing sphere decoding that identifies the colluders from the colluded signal. We evaluate the performance of the proposed WBE-based ACC fingerprints with our proposed detection algorithm through simulations, and show that the algorithm performs well at moderate noise levels. Finally, we compare our design scheme against orthogonal fingerprints and the BIBD anti-collusion codes proposed earlier, and show that the proposed WBE-based ACC and detection algorithm have better performance than BIBD-based ACC under the same configuration.

Paper Details

Date Published: 25 October 2004
PDF: 12 pages
Proc. SPIE 5601, Internet Multimedia Management Systems V, (25 October 2004); doi: 10.1117/12.571385
Show Author Affiliations
Zang Li, Rutgers Univ. (United States)
Wade K. Trappe, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 5601:
Internet Multimedia Management Systems V
John R. Smith; Tong Zhang; Sethuraman Panchanathan, Editor(s)

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