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We consider the problem of hiding information in a steganographic framework, i.e. embedding a binary message within an apparently innocuous content, in order to establish a 'suspicion-free' digital communication channel. The adversary is passive as no intentional attack is foreseen. The only threat is that she discovers the presence of a hidden(More)
This paper presents our recent works on multimedia fingerprinting, improving both the fingerprinting code and the watermarking scheme. Our first contribution focuses on deriving a better accusation process for the well known Tardos codes. It appears that Tardos orginal decoding is very conservative: its performances are guaranteed whatever the collusion(More)
This paper discusses a novel strategy for simulating rare events and an associated Monte Carlo estimation of tail probabilities. Our method uses a system of interacting particles and exploits a Feynman-Kac representation of that system to analyze their fluctuations. Our precise analysis of the variance of a standard multilevel splitting algorithm reveals an(More)
This paper estimates the minimal length of a binary proba-bilistic traitor tracing code. We consider the code construction proposed by G. Tardos in 2003, with the symmetric accusation function as improved by B. Skoric et al. The length estimation is based on two pillars. First, we consider the Worst Case Attack that a group of c colluders can lead. This(More)
This paper deals with some detection issues of watermark signals. We propose an easy way to implement an informed watermarking embedder whatever the detection function. This method shows that a linear detection function is not suitable for side information. This is the reason why we build a family of non-linear functions named JANIS. Used with a(More)
Content-Based Image Retrieval Systems used in forensics related contexts require very good image recognition capabilities. Therefore they often use the SIFT local-feature description scheme as its robustness against a large spectrum of image distortions has been assessed. In contrast, the <i>security</i> of SIFT is still largely unexplored. We show in this(More)
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