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A novel true random number generator based on a stochastic diffusive memristor.

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This study introduces a novel true random number generator using memristor stochastic switching. The device generates high-quality random bits, passing all NIST tests, ideal for secure Internet of Things applications.

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Area of Science:

  • Materials Science
  • Electrical Engineering
  • Computer Science

Background:

  • Memristor variability hinders universal memory applications.
  • Stochasticity in memristors offers potential for hardware security.
  • Previous memristor-based random number generators often require post-processing.

Purpose of the Study:

  • To propose and demonstrate a novel true random number generator (TRNG) using memristor stochasticity.
  • To leverage the stochastic delay time of threshold switching in Ag:SiO2 diffusive memristors.
  • To achieve high-quality random bit generation with improved scalability and power efficiency.

Main Methods:

  • Utilized a Ag:SiO2 diffusive memristor for its stochastic threshold switching delay time.
  • Developed a TRNG circuit based on this memristor.
  • Evaluated the generated random bits using all 15 NIST randomness tests.
  • Performed nanoparticle dynamic simulations and analytical estimates to understand stochasticity.

Main Results:

  • The memristor-based TRNG successfully generated random bits passing all 15 NIST randomness tests without post-processing.
  • The device demonstrated advantages in scalability, circuit complexity, and power consumption.
  • Stochasticity was attributed to the probabilistic detachment of silver particles from the reservoir.

Conclusions:

  • The developed memristor TRNG is a viable solution for hardware security in the Internet of Things era.
  • Harnessing memristor intrinsic variability offers a promising pathway for secure and efficient random number generation.
  • This work overcomes previous limitations of memristive-switching TRNGs by eliminating the need for post-processing.