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A Worst-Case-Aware Design Methodology for Noise-Tolerant Oscillator-Based True Random Number Generator With Stochastic Behavior Modeling
2013
IEEE Transactions on Information Forensics and Security
This paper presents a worst-case-aware design methodology for an oscillator-based true random number generator (TRNG) that produces highly random bit streams even under deterministic noise. We propose a stochastic behavior model to efficiently determine design parameters, and identify a class of deterministic noise under which the randomness gets the worst. They can be used to directly estimate the worst value of a poker test under deterministic noise without generating bit streams, which
doi:10.1109/tifs.2013.2271423
fatcat:mgz5x6u43nhtfnsi25rof6bade