Toggle Main Menu Toggle Search

Open Access padlockePrints

A Power-Gated 8-Transistor Physically Unclonable Function Accelerates Evaluation Speeds

Lookup NU author(s): Yujin ZhengORCiD, Professor Alex Yakovlev, Dr Alex Bystrov

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2023 by the authors.The proposed 8-Transistor (8T) Physically Unclonable Function (PUF), in conjunction with the power gating technique, can significantly accelerate a single evaluation cycle more than 100,000 times faster than a 6-Transistor (6T) Static Random-Access Memory (SRAM) PUF. The 8T PUF is built to swiftly eliminate data remanence and maximise physical mismatch. Moreover, a two-phase power gating module is devised to provide controllable power on/off cycles for the chosen PUF clusters in order to facilitate fast statistical measurements and curb the in-rush current. The architecture and hardware implementation of the power-gated PUF are developed to accommodate fast multiple evaluations of PUF Responses. The fast speed enables a new data processing method, which coordinates Dark-bit masking and Multiple Temporal Majority Voting (TMV) in different Process, Voltage and Temperature (PVT) corners or during field usage, hence greatly reducing the Bit Error Rate (BER) and the hardware penalty for error correction. The designs are based on the UMC 65 nm technology and aim to tape out an Application-Specific Integrated Circuit (ASIC) chip. Post-layout Monte Carlo (MC) simulations are performed with Cadence, and the extracted PUF Responses are processed with Matlab to evaluate the 8T PUF performance and statistical metrics for subsequent inclusion in PUF Responses, which comprise the novelty of this approach.


Publication metadata

Author(s): Zheng Y, Yakovlev A, Bystrov A

Publication type: Article

Publication status: Published

Journal: Journal of Low Power Electronics and Applications

Year: 2023

Volume: 13

Issue: 4

Online publication date: 29/09/2023

Acceptance date: 27/09/2023

Date deposited: 08/01/2024

ISSN (electronic): 2079-9268

Publisher: Multidisciplinary Digital Publishing Institute (MDPI)

URL: https://doi.org/10.3390/jlpea13040053

DOI: 10.3390/jlpea13040053

Data Access Statement: Not applicable.


Altmetrics

Altmetrics provided by Altmetric


Share