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

Sungho Kim, Moon Seok Kim, Yongwoo Lee, Hee Dong Kim, Yang Kyu Choi, Sung Jin Choi

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish
Article number9462143
Pages (from-to)91341-91346
Number of pages6
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

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

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