A True Random Number Generator Using Threshold‐Switching‐Based Memristors in an Efficient Circuit Design
Abstract
A true random number generator (TRNG) based on the stochastic delay and relaxation times of the threshold switching (TS) behavior in a Pt/HfO 2 /TiN memristor is proposed. The stochasticities of this device are attributed to its electron trapping and detrapping processes. This electronic‐switching‐based memristor exhibits several advantages, such as low power consumption and high reliability. A new circuit is designed to improve the simplicity, miniaturization, and lifetime of TRNG. The bitstreams collected from this TRNG pass the National Institute of Standards and Technology randomness tests without postprocessing, verifying the feasibility of adopting the memristor in hardware security applications. The bit generation rate in this work is sufficient for encryption applications requiring low power and low speed.
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tRNGs such as RRAM or MRAM are widely studied given their inherent switching stochasticity as an entropy source, which relies on material-induced variations.
“For example, tRNGs such as RRAM or MRAM, which are not Si-based complementary metal-oxide semiconductor (CMOS) devices, are widely studied given their inherent switching stochasticity as an entropy source, which relies on material-induced variations (11–18).”
From Cryptographic transistor for true random number generator with low power consumption (2024) · cites this paper as [16]
Their lack of compatibility with CMOS fabrication standards makes it difficult to apply them directly to the current CMOS logic platform used for mass production.
“Moreover, their lack of compatibility with CMOS fabrication standards makes it difficult to apply them directly to the current CMOS logic platform used for mass production.”
From Cryptographic transistor for true random number generator with low power consumption (2024) · cites this paper as [16]
These tRNGs require a few entropy extraction circuits, each of which consumes power at the milliwatt level.
“However, these tRNGs require a few entropy extraction circuits, each of which consumes power at the milliwatt level.”
From Cryptographic transistor for true random number generator with low power consumption (2024) · cites this paper as [16]
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- Authors
- Woo, K. S., Wang, Y., Kim, J., Kim, Y., Kwon, Y. J., Yoon, J. H., Kim, W., & Hwang, C. S.
- Affiliations
- Seoul National University (KR)
- Corresponding author
- Hwang, Cheol Seong
- Venue
- Advanced Electronic Materials
- Publisher
- Wiley
- Published
- 2018-11-28
- Volume
- 5
- Issue
- 2
- ISSN
- 2199-160X (ISSN-L)
- OpenAlex
- W2902832852
- Cited by
- 64
- References
- 26
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 14 · 2023: 12 · 2022: 4 · 2021: 10 · 2020: 4 · 2019: 1
- FWCI
- 1.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Advanced Electronic Materials (publishedVersion)
- Funders
- Korea Institute of Science and Technology (2E27731)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Computer Science › Hardware and Architecture › Physical Unclonable Functions (PUFs) and Hardware Security
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Ferroelectric and Negative Capacitance Devices
- Keywords
- true random number generator, memristors, threshold switching, electron trapping and detrapping, stochastic delay, relaxation time, hardware security, randomness testing, low-power encryption, circuit design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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