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Cryptography-based content protection is an efficient means to protect multimedia content during transport. Nevertheless, content is eventually decrypted at rendering time, leaving it vulnerable to piracy e.g. using a camcorder to record movies displayed on an LCD screen. Such type of piracy naturally imprints a visible flicker signal in the pirate video due to the interplay between the rendering and acquisition devices. The parameters of such flicker are inherently tied to the characteristics of the pirate devices such as the backlight of the LCD screen and the read-out time of the camcorder. In this article, we introduce a forensic methodology to estimate such parameters by analyzing the flicker signal present in pirate recordings. Experimental results clearly showcase that the accuracy of these estimation techniques offers efficient means to tell-tale which devices have been used for piracy thanks to the variety of factory settings used by consumer electronics manufacturers. Figure 1: Flicker artifact when recording an LCD screen displaying a uniformly gray frame with a camcorder.

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Non-blind watermark detection is still relevant in some applications e.g. traitor tracing. In this case, the auxiliary metadata sent to the detector reveals something about the original content. In this paper, we investigate whether such side-information could also be exploited for registration purpose.To this end, we take a reference non-blind video watermarking system for H.264 AVC CABAC video and show that the watermark auxiliary information could be used in a fingerprint-based registration framework. Our proposed registration strategy operates in two steps: first, identify in the candidate video the best match for each watermarked frame of the master video ; second, discard frames which are most likely to be misregistered (for instance, watermarked frames which have been deleted in the candidate video).In comparison with conventional fingerprint-based techniques, the advantage of this strategy is twofold: (i) the accuracy of the registration naturally adapts to the watermark information density carried by each frame and (ii) it does not require additional storage overhead. Reported experimental results clearly demonstrate that the proposed registration approach largely outperforms other ones relying on independent video fingerprints.