Summary
Digital fingerprinting is a technique whereby a unique digital fingerprint associated with each legitimate user is hidden in the multimedia content so that consumers who redistribute the content illegally can be traced. Typically, robust watermarking techniques are used to embed digital fingerprints in order to provide resilience 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), was proposed for use with code-modulated data embedding. Two important issues need to be considered when designing ACC: accommodating as many users as possible for a given fingerprint dimensionality, and identifying the colluders effectively from the colluded signal. In this chapter, 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). In order to identify the colluders when employing WBE-based ACC, we further propose a powerful detection algorithm utilizing sphere decoding to identify the colluders from the colluded signal. We compare our WBE-ACC against orthogonal fingerprints and BIBD-based anti-collusion codes via simulations, and show that the proposed WBE-based ACC and detection algorithm gives a better performance than the BIBD-based ACC under the same configuration.
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Li, Z., Trappe, W. (2010). WBE-Based Anti-collusion Fingerprints: Design and Detection. In: Sencar, H.T., Velastin, S., Nikolaidis, N., Lian, S. (eds) Intelligent Multimedia Analysis for Security Applications. Studies in Computational Intelligence, vol 282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11756-5_14
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DOI: https://doi.org/10.1007/978-3-642-11756-5_14
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