Open AccessA High‐Speed True Random Number Generator Based on a Cu x Te 1− x Diffusive Memristor
Author(s) -
Woo Kyung Seok,
Kim Jaehyun,
Han Janguk,
Choi Jin Myung,
Kim Woohyun,
Hwang Cheol Seong
Publication year - 2021
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202100062
Subject(s) - random number generation , randomness , memristor , nucleation , generator (circuit theory) , nanotechnology , materials science , statistical physics , computer science , biological system , optoelectronics , physics , mathematics , power (physics) , algorithm , statistics , quantum mechanics , thermodynamics , biology
Herein, a true random number generator (TRNG) based on a Cu x Te 1− x diffusive memristor (DM) using its threshold switching (TS) behavior is reported. The intrinsic stochasticity of the TS behavior contributes to the randomness of the TRNG system. The switching behavior is discussed through field‐induced nucleation theory and surface diffusion dynamics. Demonstrating the performance of TRNG as a hardware security application, the DM‐based TRNG passes all 15 National Institute of Standards and Technology randomness tests without any post‐processing step, even in high‐temperature conditions. Moreover, a nonlinear‐feedback shift register is implemented for a high‐speed TRNG, producing the highest rate among the reported volatile‐memristor‐based TRNGs.