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A Magnetic Tunnel Junction based True Random Number Generator with conditional perturb and real-time output probability tracking
Abstract
This work experimentally demonstrates for the first time a True Random Number Generator (TRNG) based on the random switching probability of Magnetic Tunnel Junctions (MTJs). A conditional perturb and real-time output probability tracking scheme is proposed to enhance the reliability, speed, and power consumption while maintaining a 100% bit efficiency.
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“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 [11]
In the citing paper
“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 [11]
In the citing paper
“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 [11]
Citations
Cites
Untitled work
yoshida (2009) · IRPS
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yuasa (2013) · IEDM
UnresolvedUntitled work
rukhin (2010) · NIST Pub
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hunter (1999) · IRPS
UnresolvedUntitled work
zhao (2011) · JAP
UnresolvedUntitled work
yang (2014) · ISSCC
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Items 101–125 of 125
High-Accuracy Deep Belief Network: Fuzzy Neural Networks Using MRAM-Based Stochastic Neurons
Pourmeidani, H., & DeMara, R. F. (2021) · IEEE Journal on Exploratory Solid-State Computational Devices and Circuits · doi:10.1109/jxcdc.2021.3117489 · Cited by 3
Yoo, S., Holla, A., Sanyal, S., Kim, D. E., Iacopi, F., Biswas, D., Myers, J., & Roy, K. (2025) · ACM/IEEE Design Automation Conference (DAC) · doi:10.1109/dac63849.2025.11132522 · Cited by 2
Bipolar Random Signal Generation With Electrical Operation Based on Two Magnetic Tunnel Junctions
Jian, J., Yuan, X., Chai, Z., et al. (2024) · IEEE Electron Device Letters · doi:10.1109/led.2024.3515147 · Cited by 2
“Most existing RSGs are designed for binary signal with only two states [20], [21], [22].”
FeFET-based Process-in-Memory Architecture for Low-Power DNN Training
Zokaee, F., Li, B., & Chen, F. (2021) · IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH) · doi:10.1109/nanoarch53687.2021.9642234 · Cited by 2
NIST SP 800-90B Compliant Perpendicular Magnetic Tunnel Junction Based True Random Number Generator
Jia, Q., Egan, S., Lv, Y., & Wang, J.-P. (2025) · 2025 IEEE 36th Magnetic Recording Conference (TMRC) · doi:10.1109/tmrc66824.2025.11192720 · Cited by 1
“Spintronic devices, particularly magnetic tunnel junctions (MTJs), offer a promising alternative due to their low power consumption and rapid switching capabilities [2]-[11].”
Self-citationUnified PUF and TRNG Design Using SOT-MTJ Crossbar Array
Das, K. K., Nisar, A., Kaushik, B. K., Chattopadhyay, A., & Zahoor, F. (2025) · IEEE Transactions on Magnetics · doi:10.1109/tmag.2025.3574994 · Cited by 1
“Incorpo-rating adaptive calibration techniques, such as feedback-based control or current tuning, can help maintain reliable operation under varying conditions [41], [42].”
Yang, S.-H., Bao, Y.-W., Humianto, E., Prabhakar, A., & Yang, H. (2026) · Nature Communications · doi:10.1038/s41467-026-71128-1 · Cited by 2
“…random number generation is a key ingredient of probabilistic computing, magnetic tunnel junctions (MTJs) emerge as promising spintronic candidates due to their energy and area ef fi - ciency, rooted in their inherent stochastic switching behavior and tunable switching probabilities 31 – 34 .”
Cagli, C., & Perniola, L. (2022) · Springer handbooks · doi:10.1007/978-3-030-79827-7_17 · Cited by 1
eNVM based In-memory Computing for Intelligent and Secure Computing Systems
Huang, K., & Qin, C. (2019) · IEEE International System-on-Chip Conference (SOCC) · doi:10.1109/socc46988.2019.1570557582 · Cited by 1
“%) is controlled by tuning the write pulse duration or amplitude, which can be leveraged to create TRNGs with true randomness for security applications [33], [34].”
BackgroundBazzi, H., Postel-Pellerin, J., Aziza, H., Moreau, M., & Harb, A. (2020) · Proceedings · doi:10.1109/dft50435.2020.9250726 · Cited by 1
“To this aim, real time voltage tracking techniques such as the one presented in [17] can be used.”
MethodHardware implementation of Bayesian network building blocks with stochastic spintronic devicesPreprint
Debashis, P., Ostwal, V., Faria, R., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.08418 · Cited by 1
Stochastic-Based Computing with Emerging Spin-Based Device Technologies
Bai, Y. D. (2016) · Journal of International Crisis and Risk Communication Research
AQuRate: MRAM-based Stochastic Oscillator for Adaptive Quantization Rate Sampling of Sparse SignalsPreprint
Salehi, S., Zand, R., Zaeemzadeh, A., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.00971
“In recent years the use of superparamagnetic MTJs that are not thermally stable have been experimentally and theoretically investigated in search of functional spintronic devices [5, 7–9, 12, 17, 21, 22].”
BackgroundPyle, S. D. (2019) · Journal of International Crisis and Risk Communication Research
Digital readout optimization of the random resistive states in magnetic tunnel junction
Egler, T., Dittmann, H., & Useinov, A. (2019) · Solid-State Electronics · doi:10.1016/j.sse.2019.107666
A Programmable Approximate Calculation Unit Employing Time-Encoded Stochastic Computing Elements
Nguyen, V. T., Erlina, T., Zhang, R., et al. (2019) · International Symposium on Computing and Networking Workshops (CANDARW) · doi:10.1109/candarw.2019.00024
“Recently, the stochastic computing (SC) technologies are widely considered as practical solutions for approximate computing with high efficiency in hardware [9]–[12].”
BackgroundMethodCustom CMOS and Post-CMOS Crossbar Circuits for Resource-Constrained Hardware Security Primitives
Yang, K. (2019) · Technical digest - International Electron Devices Meeting/Technical digest · doi:10.1109/iedm19573.2019.8993473
Divyanshu, D., Kumar, R., Khan, D., et al. (2023) · IEEE International Conference on Smart Mobility (SM) · doi:10.1109/sm57895.2023.10112292
“For the first time, a TRNG based on the random switching probability of MTJs with conditional perturb was experimentally demonstrated [12].”
MethodToward Spintronics Non-volatile Computing-in-Memory Architecture
Wu, B., Zhu, H., Yu, T., & Liu, W. (2023) · Springer eBooks · doi:10.1007/978-3-031-42478-6_3
High-frequency spin transport in thin aluminum calculated by spin drift-diffusion equation
Hao, R., & Victora, R. H. (2025) · Applied Physics Letters · doi:10.1063/5.0251897
Rhythms and oscillations : a vision for nanoelectronics
Vodenicarevic, D. (2017) · theses.fr (ABES) · doi:10.70675/1edcb840z2d2fz466cz92d8zf77ced4ff80d · Cited by 3
Resistive memory co-design in CMOS technologies
Bazzi, H. (2020) · theses.fr (ABES) · doi:10.70675/78f0c866z7434z4bd7z84b7zb84b151fd845
Magnetic-Tunnel-Junction-Based Probabilistic Processor for Efficient Embodied Evolution
Bao, Y., Yang, S., Humianto, E., & Yang, H. (2026) · Nano Letters · doi:10.1021/acs.nanolett.6c00275
Jia, Q., Egan, S., Lv, Y., & Wang, J. (2026) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2026.3715464
“Prior e ff orts have attempted to address this by using negative-feedback control circuits to fix the switching probability dynamically [32], [33], [34].”
Self-citation
Metadata
- Authors
- Choi, W. H., Lv, Y., Kim, J., Deshpande, A., Kang, G., Wang, J.-P., & Kim, C. H.
- Affiliations
- University of Minnesota (US)
- Venue
- 2014 IEEE International Electron Devices Meeting
- Publisher
- IEEE
- Published
- 2014-12
- Pages
- 12.5.1-12.5.4
- ISSN
- 0163-1918 (ISSN-L)
- OpenAlex
- W2004596214
- Cited by
- 128
- References
- 6
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 7 · 2023: 12 · 2022: 8 · 2021: 13 · 2020: 11 · 2019: 20 · 2018: 16 · 2017: 16 · 2016: 10 · 2015: 5
- FWCI
- 6.75
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Technical digest - International Electron Devices Meeting/Technical digest (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Computer Science › Hardware and Architecture › Physical Unclonable Functions (PUFs) and Hardware Security
- Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Magnetic properties of thin films
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Keywords
- true random number generator, magnetic tunnel junctions, power consumption, hardware randomness
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