Low-Power True Random Number Generator Based on Randomly Distributed Carbon Nanotube Networks

Abstract

Although the intrinsic variability in nanoelectronic devices has been a major obstacle and has prevented mass production, this natural stochasticity can be an asset in hardware security applications. Herein, we demonstrate a true random number generator (TRNG) based on stochastic carrier trapping/detrapping processes in randomly distributed carbon nanotube networks. The bitstreams collected from the TRNG passed all the National Institute of Standards and Technology randomness tests without post-processing. The random bit generated in this study is sufficient for encryption applications, particularly those related to the Internet of Things and edge computing, which require significantly lower power consumption.

Keywords

• Carbon nanotube network
• random number generator
• stochastic carrier trapping