RTN in Scaled Transistors for On-Chip Random Seed Generation

Abstract

Random numbers play a vital role in cryptography, where they are used to generate keys, nonce, one-time pads, and initialization vectors for symmetric encryption. The quality of random number generator (RNG) has significant implications on vulnerability and performance of these algorithms. A pseudo-RNG uses a deterministic algorithm to produce numbers with a distribution very similar to uniform. True RNGs (TRNGs), on the other hand, use some natural phenomenon/process to generate random bits. They are nondeterministic, because the next number to be generated cannot be determined in advance. In this paper, a novel on-chip noise source, random telegraph noise (RTN), is exploited for simple and reliable TRNG. RTN, a microscopic process of stochastic trapping/detrapping of charges, is usually considered as a noise and mitigated in design. Through physical modeling and silicon measurement, we demonstrate that RTN is appropriate for TRNG, especially in highly scaled MOSFETs. Due to the slow speed of RTN, we purpose the system for on-chip seed generation for random number. Our contributions are: 1) physical model calibration of RTN with comprehensive 65- and 180-nm transistor measurements; 2) the scaling trend of RTN, validated with silicon data down to 28 nm; 3) design principles to achieve 50% signal probability by using intrinsic RTN physical properties, without traditional postprocessing algorithms, the generated sequence passes the National Institute of Standards and Technology (NIST) tests; and 4) solutions to manage realistic issues in practice, including multilevel RTN signal, robustness to voltage and temperature fluctuations and the operation speed.