The DOI matches its Crossref record, with a small difference in title or year; 24 of the 26 references it cites were found in a registry or an index.
$\mu $ RNG: A 300–950 mV, 323 Gbps/W All-Digital Full-Entropy True Random Number Generator in 14 nm FinFET CMOS
Abstract
This paper describes μRNG, an ultra-lightweight all-digital full-entropy true-random number generator (TRNG), fabricated in 14 nm high-k/metal-gate FinFET CMOS, targeted for on-die generation of cryptographic keys in energy-constrained IoT and wearable platforms. The μRNG combines the entropy of multiple independent sources to generate an output bitstream that is indistinguishable from an ideal unbiased entropy source. Three independent self-calibrating all-digital entropy sources, coupled with XOR feedback shift-register based correlation suppressors and an in-line compact Barak-Impagliazzo- Wigderson (BIW) extractor enable ultra-low energy consumption of 3 pJ/full-entropy bit with a dense layout occupying 1008 μm2, while achieving: (i) 162.5 Mbps full-entropy throughput at 1.3 GHz operation, with total power consumption of 1.5 mW and leakage power component of 90 μW, measured at 0.75 V, 25°C, (ii) mutually uncorrelated raw bitstreams from the three entropy sources with phi-coefficient cross-correlation∞> 0.99, (iv) hysteresis-free extracted output for lags 1-1000, with ACF ~0 within 95% confidence bounds of a Gaussian distribution (μ = 0, σ2= 0.002), (v) wide operating supply voltage range of 300-950 mV with throughput scaling to 225 Mbps at 950 mV and robust subthreshold voltage performance of 400 Kbps, 4 μW, measured at 300 mV, 25°C, (vi) peak energy-efficiency of 323 Gbps/W at near-threshold voltage of 400 mV, with full-entropy throughput of 8.6 Mbps, total power consumption of 27 μW, (vii) 6.5× reduction in gate count and 5.4× lower energy consumption compared to conventional AES-based entropy extractors.
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“Subsequently, Intel improved this TRNG using in-line decorrelators and a lightweight BIW extractor.It demonstrated that this TRNG could provide a throughput of 162.5 Mbps at 1.3 GHz operation, with 1.5 mW total power consumption and a 90 µW leakage component [11].”
From True Random Number Generators Using Electrical Noise (2019) · cites this paper as [11]
Citations
Cites
Bassham, L. E., Rukhin, A. L., Soto, J., Nechvatal, J. R., Smid, M. E., Barker, E. B., Leigh, S. D., Levenson, M., Vangel, M., Banks, D. L., et al. (2010) · NIST Special Publication 800-22 Revision 1a · doi:10.6028/nist.sp.800-22r1a · Cited by 3,617
Mathematical Methods of Statistics.
David, F. N., & Cramer, H. L. (1947) · Biometrika · doi:10.2307/2332454 · Cited by 1,782
Power-Up SRAM State as an Identifying Fingerprint and Source of True Random Numbers
Holcomb, D. E., Burleson, W. P., & Fu, K. (2008) · IEEE Transactions on Computers · doi:10.1109/tc.2008.212 · Cited by 846
A Provably Secure True Random Number Generator with Built-In Tolerance to Active Attacks
Sunar, B., Martin, W. J., & Stinson, D. R. (2007) · IEEE Transactions on Computers · doi:10.1109/tc.2007.250627 · Cited by 673
Natarajan, S., Agostinelli, M., Akbar, S. A., Bost, M. C., Bowonder, A., Chikarmane, V., Chouksey, S., Dasgupta, A., Fischer, K., Fu, Q., et al. (2014) · Technical digest - International Electron Devices Meeting/Technical digest · doi:10.1109/iedm.2014.7046976 · Cited by 543
Recommendation for the Entropy Sources Used for Random Bit Generation
Turan, M. S., Barker, E., Kelsey, J., McKay, K. A., Baish, M. L., & Boyle, M. (2018) · NIST Special Publication 800-90B · doi:10.6028/nist.sp.800-90b · Cited by 489 · cited 2×
“The Markov test from NIST SP800–90B [26] measures dependencies between consecutive μRNG outputs by estimating the min-entropy present in a given k-long chain of output bits.”
MethodA noise-based IC random number generator for applications in cryptography
Petrie, C. S., & Connelly, J. A. (2000) · IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications · doi:10.1109/81.847868 · Cited by 487
Mathew, S. K., Srinivasan, S., Anders, M. A., Kaul, H., Hsu, S. K., Sheikh, F., Agarwal, A., Satpathy, S., & Krishnamurthy, R. K. (2012) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2012.2217631 · Cited by 195
Self-citationNew Methods for Digital Generation and Postprocessing of Random Data
Golic, J. D. J. (2006) · IEEE Transactions on Computers · doi:10.1109/tc.2006.164 · Cited by 188
High-Speed True Random Number Generation with Logic Gates Only
Dichtl, M., & Golić, J. D. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-74735-2_4 · Cited by 182
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2 of the 26 references couldn’t be matched to a known paper.
Research works printed but not linked: 9
- fujita, 2004, Si nanodevices for RNG circuits for cryptographic security, IEEE ISSCC Dig, 294
- liu, 2011, A TRNG using time-dependent dielectric breakdown, Symp VLSI Circuits Dig, 216
- yang, 2015, A robust ?40 to 120°C all-digital true random number generator in 40 nm CMOS, Symp VLSI Circuits Dig, 248c
- yang, 2014, A 23 Mb/s 23 pJ/b fully synthesized TRNG in 28 nm and 65 nm CMOS, IEEE ISSCC Dig, 280
- brederlow, 2006, A low-power TRNG using random telegraph noise of single oxide-traps, IEEE ISSCC Dig, 536
- mathew, 2015, $\mu $ RNG: A 300-950 mV 323 Gbps/W all-digital fullentropy TRNG in 14 nm FinFET CMOS, Proc ESSCIRC, 116
- cox, 2011, Intel’s digital random number generator, Hot Chips 11 Symp High-Performance Chips
- srinivasan, 2010, 2.4 GHz 7 mW all-digital PVT-variation tolerant TRNG in 45 nm CMOS, Symp VLSI Circuits Dig, 216
- tokunaga, 2007, TRNG with a metastability-based quality control, IEEE ISSCC Dig, 404
Cited by
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Items 101–102 of 102
Wang, Z., Chen, P., Ma, Q., Wu, Z., Guo, W., Zou, J., Wang, H., Hao, Y., Yang, Y., Jiang, M., et al. (2026) · Advanced Functional Materials · doi:10.1002/adfm.77093
Kim, S.-I., Hong, I., Lee, S.-W., You, H.-J., An, U.-S., Han, J.-A., Kim, M., Ryu, S., & Choi, Y. (2026) · ACS Nano · doi:10.1021/acsnano.6c02362
Metadata
- Authors
- Mathew, S. K., Johnston, D., Satpathy, S., Suresh, V., Newman, P., Anders, M. A., Kaul, H., Agarwal, A., Hsu, S. K., Chen, G., & Krishnamurthy, R. K.
- Affiliations
- Intel (United States) (US)
- ORCID
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2016-07
- Volume
- 51
- Issue
- 7
- Pages
- 1695-1704
- ISSN
- 0018-9200 (ISSN-L)
- 1558-173X
- OpenAlex
- W2401371495
- Cited by
- 102
- References
- 26
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 12 · 2023: 9 · 2022: 15 · 2021: 14 · 2020: 14 · 2019: 13 · 2018: 7 · 2017: 3
- FWCI
- 11.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal of Solid-State Circuits (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Hardware and Architecture › Physical Unclonable Functions (PUFs) and Hardware Security
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Low-power high-performance VLSI design
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Keywords
- true random number generator, low-power electronics, near-threshold operation, subthreshold operation, wide supply voltage range, energy efficiency, cryptographic key generation, Internet of Things, wearable devices, 14nm FinFET
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