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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Algorithms for post-quantum commutative group actions
Orateur : Marc Houben - Inria Bordeaux
At the historical foundation of isogeny-based cryptography lies a scheme known as CRS; a key exchange protocol based on class group actions on elliptic curves. Along with more efficient variants, such as CSIDH, this framework has emerged as a powerful building block for the construction of advanced post-quantum cryptographic primitives. Unfortunately, all protocols in this line of work are[…] -
Endomorphisms via Splittings
Orateur : Min-Yi Shen - No Affiliation
One of the fundamental hardness assumptions underlying isogeny-based cryptography is the problem of finding a non-trivial endomorphism of a given supersingular elliptic curve. In this talk, we show that the problem is related to the problem of finding a splitting of a principally polarised superspecial abelian surface. In particular, we provide formal security reductions and a proof-of-concept[…]-
Cryptography
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