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An All-Digital Unified Physically Unclonable Function and True Random Number Generator Featuring Self-Calibrating Hierarchical Von Neumann Extraction in 14-nm Tri-gate CMOS
Abstract
This paper describes a unified static/dynamic entropy generator based on a 512-b common entropy source (ES) array fabricated in 14-nm tri-gate CMOS with reconfigurable and adaptive post-processing circuits implemented on Arria 10 FPGA, targeted for flexible and secure privacy preserving mutual authentication on compact trusted mote platforms at the edge of internet of things. Several conditioning techniques that include temporal majority voting (TMV)-assisted ES array segregation with integrated bias tracking, three-way in-line self-calibration for tolerance to process–voltage–temperature variation, tri-level hierarchical Von Neumann (VN) extraction to maximize entropy harvesting, soft-dark bit masking for improving physically unclonable function (PUF) stability, and selective stress hardening to co-optimize the ES array for static-dynamic entropy with bias aware device aging enable simultaneous PUF and true random number generator (TRNG) operation with 1.48 and 0.56 Gb/s throughput, respectively, measured at 650 mV, 70 °C. The all-digital design with a compact layout footprint of 2114$\mu \text{m}^{2}$facilitates seamless integration in area constrained system-on-chips while achieving: 1) 25% area savings over conventional separate PUF and TRNG implementations; 2) cryptographic quality TRNG stream that passes all NIST randomness tests with 0.38 average p-value; 3)$1.6\times $higher extractor performance at$9\times $lower area with 750-gate hierarchical VN circuit over conventional light-weight entropy extractors; 4) 0.9996/0.99997 static/dynamic Shannon entropy indicating unbiased PUF/TRNG streams; 5) ultra-low energy consumption of 2.5 and 0.46 pJ/bit measured at 650 mV, 70 °C in TRNG and PUF modes; 6) 40% higher TRNG throughput with three-way self-calibration featuring coarse-grain column swap, fine-grain incremental ES substitution, and residual entropy recycling; 7) resistance to power injection attacks as measured by 64% higher performance over un-calibrated design in the presence 200-mV supply noise; 8) 2.8% PUF bit-error measured at 0.55–0.75 V, 25 °C–110 °C with 15-way TMV and soft dark-bit masking over a window of 100 cycles; 9)$14.8\times $inter and intra-PUF hamming distance separation; and 10) 56% reduction in discarded ES cells with selective stress hardening to opportunistically reinforce/nullify pre-existing bias in PUF/TRNG candidate cells. To our knowledge, this is the first reported unified PUF-TRNG implementation enabling simultaneous generation of high-entropy chip-ID and encryption keys in real time.
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“Note that those entropy sources rely on operation-induced variations (19–23).”
From Cryptographic transistor for true random number generator with low power consumption (2024) · cites this paper as [22]
In the citing paper
“In contrast, Si-CMOS–based tRNGs use circuitry that uses various types of entropy sources, such as timing jitter, chaotic maps, metastability, or noise jitter from SRAM bit-line leakages for low power consumption.”
From Cryptographic transistor for true random number generator with low power consumption (2024) · cites this paper as [22]
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“They show excellent randomness and insensitivity to fabrication-induced variability.”
From Cryptographic transistor for true random number generator with low power consumption (2024) · cites this paper as [22]
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Self-citationCheng, K., Huang, Y., Yang, Z., Wang, L., Ren, H., Shan, X., Mak, P., Chen, Y., & Li, B. (2026) · Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference · doi:10.1109/isscc49663.2026.11409134 · Cited by 1
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2019 Index IEEE Journal of Solid-State Circuits Vol. 54
(2019) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2019.2956675
Kumar, D., Chaurasia, U. K., Mishra, S., Patel, P. S., Misra, P. K., & Goswami, M. (2021) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126621502856
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Sridevi, G. M., Ashoka, D. V., & Vijaya, A. P. B. (2022) · Karbala International Journal of Modern Science · doi:10.33640/2405-609x.3223
(2019) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2019.2905124
Anusha, B., & Manindar, M. A. (2022) · Algorithms for intelligent systems · doi:10.1007/978-981-19-1669-4_33
Wang, X., Zhang, R., & Shinohara, H. (2023) · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · doi:10.1587/transfun.2023kep0011
5G-SRNG: 5G Spectrogram-based Random Number Generation for Devices with Low Entropy Sources
Çatak, F. Ö., Çatak, E., & Elezaj, O. (2023) · IEEE International Conference on Omni-layer Intelligent Systems (COINS) · doi:10.1109/coins57856.2023.10189262
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Hunt-Schroeder, E., & Xia, T. (2025) · Microelectronics Reliability · doi:10.1016/j.microrel.2025.115592
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Talay, Y. (2025) · Analog Integrated Circuits and Signal Processing · doi:10.1007/s10470-024-02298-5
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Kim, J., & Chen, V. (2025) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2025.3602728
Zhang, R., Cao, Y., Zhang, H., Cheng, Q., Nishizawa, S., Niitsu, K., & Shinohara, H. (2025) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2025.3621604
Metadata
- Authors
- Satpathy, S. K., Mathew, S. K., Kumar, R., Suresh, V., Anders, M. A., Kaul, H., Agarwal, A., Hsu, S., Krishnamurthy, R. K., & De, V.
- Affiliations
- Intel (United States) (US)
- ORCID
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2019-04
- Volume
- 54
- Issue
- 4
- Pages
- 1074-1085
- ISSN
- 0018-9200 (ISSN-L)
- 1558-173X
- OpenAlex
- W2908207594
- Cited by
- 114
- References
- 48
- Citations by year
- 2026: 15 · 2025: 21 · 2024: 13 · 2023: 14 · 2022: 16 · 2021: 15 · 2020: 17 · 2019: 3
- FWCI
- 12.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- 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
- physical unclonable functions, true random number generator, entropy source, self-calibration, device aging, PVT variation, mutual authentication, Internet of Things security, low-power electronics
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