Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry

Section: Contracts and Grants with Industry

Security and reliability in digital watermarking (NEBBIANO) — ANR Sécurité

Participants : Frédéric Cérou, Arnaud Guyader, Cyrille Jégourel, Fida El Haje Hussein.

See  3.4 , 4.2 , 6.3 and  6.4 .

INRIA contract ALLOC 2229 — January 2007 to December 2009.

Arnaud Guyader is coordinator of this ANR project. This is a collaboration with Teddy Furon from INRIA Rennes Bretagne Atlantique (project–team TEMICS) and Pierre Del Moral from INRIA Bordeaux Sud–Ouest (project–team ALEA). Besides these project–teams, the other partner is LIS–INPG in Grenoble.

There are mainly two strategic axes in NEBBIANO : watermarking and independent component analysis, and watermarking and rare event simulations. To protect copyright owners, user identifiers are embedded in purchased content such as music or movie. This is basically what we mean by watermarking. This watermarking is to be “invisible” to the standard user, and as difficult to find as possible. When content is found in an illegal place (e.g. a P2P network), the right holders decode the hidden message, find a serial number, and thus they can trace the traitor, i.e. the client who has illegally broadcast their copy. However, the task is not that simple as dishonest users might collude. For security reasons, anti–collusion codes have to be employed. Yet, these solutions (also called weak traceability codes) have a non–zero probability of error defined as the probability of accusing an innocent. This probability should be, of course, extremely low, but it is also a very sensitive parameter: anti–collusion codes get longer (in terms of the number of bits to be hidden in content) as the probability of error decreases. Fingerprint designers have to strike a trade–off, which is hard to conceive when only rough estimation of the probability of error is known. The major issue for fingerprinting algorithms is the fact that embedding large sequences implies also assessing reliability on a huge amount of data which may be practically unachievable without using rare event analysis. Our task within this project is to adapt our methods for estimating rare event probabilities to this framework, and provide watermarking designers with much more accurate false detection probabilities than the bounds currently found in the literature. We have already applied these ideas to some randomized watermarking schemes and obtained much sharper estimates of the probability of accusing an innocent.

A patent “Validation de schémas de verrous numériques en watermarking et fingerprinting” has been submitted by INRIA and by université de Rennes 2.


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