Description
The talk examines power noise modelling through Gaussian Processes for secure True Random Number Generators.
While revisiting one-sided fractional Brownian motion, we obtain novel contributions by quantifying posterior uncertainty in exact analytical form, establishing quasi-stationary properties, and developing rigorous time-frequency analysis. These results are applied to model oscillator fluctuations of power-noise type, enabling closed-form entropy expressions for TRNGs and a novel GPU-accelerated simulation technique valuable for studying non-standard post-processing.
This work bridges machine learning techniques and signal processing to solve hardware security applications.
Keywords
Gaussian Process, Power Noise, True Random Number Generator, Fractional Brownian Motion, Entropy Estimation, Hardware Security, GPU Acceleration
Infos pratiques
Prochains exposés
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!!! Reporté !!! Encryption homomorphe sans bruit à l'aide de groupes
Orateur : Pierre Guillot - Ravel Technologies (dispo Université de Strasbourg, IRMA)
Je vais rappeler les travaux de Nuida et Ostrovski sur l'utilisation des groupes pour l'élaboration de schémas cryptographiques homomorphes. Je vais présenter nos travaux qui fournissent des encodages à la fois plus efficaces et plus généraux, et qui déterminent exactement quels groupes peuvent être utilisés. Puis je vais discuter GRAFHEN, un protocole qui utilise ces idées. Je dirai juste[…]-
Cryptography
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MIKE: An efficient and compact NIKE Based on a Commutative Monoidal Action
Orateur : Jonathan Komada Eriksen - COSIC, KU Leuven
Robert recently described a powerful correspondence between certain (Hermitian) modules and (polarized) abelian varieties, which simultaneously generalizes both the class-group action underlying protocols such as CSIDH, and the Deuring correspondence, underlying protocols such as SQIsign. Using this correspondence, he also proposed how to construct a post-quantum NIKE, called MIKE, which, at a[…]-
Cryptography
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