2014 · 66 citations · 14 references
ComputingComputer EngineeringComputer ScienceComputer SecurityHardware SecuritySecurity ArchitectureEmbedded SecurityEmbedded System SecurityLow-power Digital Circuit DesignNoise In Electronic DevicesNoise In Semiconductor DevicesRandom Number GenerationBias DetectionElectronics NoiseHardware Random Number GeneratorsRandomness ExtractionSecure Random Number GenerationSelf-calibrationTrue Random Number GenerationVoltage
True random number generators (TRNGs) are needed for a variety of security applications and protocols. The quality (randomness) of TRNGs depends on sensitivity to random noise, environmental conditions, and aging. Random sources of noise improve TRNG quality. In older or more mature technologies, the random sources are limited resulting in low TRNG quality. Prior work has also shown that attackers can manipulate voltage supply and temperature to bias the TRNG output. In this paper, we propose bias detection mechanisms and a technology independent TRNG (TI-TRNG) architecture. The TI-TRNG enhances power supply noise for older technologies and uses a self-calibration mechanism that reduces bias in TRNG output due to aging and attacks. Experiment results on 130nm, 90nm, and 45nm FPGAs demonstrate the quality of random sequences from the TI-TRNG across aging and different environmental conditions.
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Kelin J. Kuhn, M.D. Giles, D. Becher et al. · IEEE Transactions on Electron Devices · 2011 · 365 citations
Engineering, Computer Engineering, Electrical Engineering +17