DVFT: A Lightweight Solution for Power-Supply Noise-Based TRNG Using Dynamic Voltage Feedback Tuning System

作者：Tehranipoor Fatemeh^*; Wortman Paul; Karimian Nima; Yan Wei; Chandy John A

来源：IEEE Transactions on Very Large Scale Integration Systems, 2018, 26(6): 1084-1097.

DOI：10.1109/TVLSI.2018.2804258

• Control feedback system
• NIST test
• power-supply
• variation
• random noise
• true random number generation

True random number generators (TRNGs) are central to many computing applications, particularly in security domains such as cryptography. In this paper, we consider the design and implementation of a low-cost and lightweight TRNG. In the interest of being thorough, we examined six different power supplies in order to verify the noncyclostationary behavior of the voltage sources. Our novel TRNG model is based on power-supply variations (noise behavior) and self-adjusting operation. The benefit of our novel design is that it is simple and easy to implement and there is little to no additional cost required to incorporate the TRNG into existing circuitry. In addition, dynamic voltage feedback tuning (DVFT) allows for feasibility and robustness of our model. The cumulative effect of these benefits is the practicality of the entire power-supply noise-based TRNG system. We then validate the results of our theoretical model and experimental setup to show that there is a highentropy rate based on the findings from the NIST statistical test suite. Based on our observations and results, our DVFT power-supply noise-based TRNG model has the potential to be used in critical applications while also having the advantage of simplicity and practicality.

• 出版日期2018-6