A Weak-PUF-Assisted Strong PUF with Inherent Security Using Metastability Implemented on FPGAs

Physical unclonable functions (PUFs) are emerging as highly promising lightweight hardware security primitives that offer novel information security solutions. PUFs capitalize on the intrinsic physical variations within circuits to generate unpredictable responses. Nevertheless, diverse PUF types often encounter difficulties in concurrently fulfilling multiple performance requisites. As is well known, strong PUFs possess significantly larger challenge–response pair (CRP) set sizes. However, they are vulnerable to machine learning (ML) attacks. Conversely, weak PUFs generate responses with superior randomness, yet their CRP sets are inadequate to satisfy the demands of practical applications. This paper presents a newly devised double-latch PUF (DL-PUF) to address this issue. This design significantly enhances both the CRP set size and security performance. The available CRPs of the DL-PUF design can reach up to 264, and its robust security features are also demonstrated in this paper. We have implemented this design on twelve 45 nm Xilinx Spartan 6 XC6SLX25 FPGAs. The experimental results indicate that our proposed DL-PUF performs well in terms of reliability, uniqueness, uniformity, and randomness. Additionally, three machine learning algorithms were employed to conduct comprehensive tests on the DL-PUF. The results reveal its excellent resilience against machine learning attacks.

Authors

Institutions

Publication Details

Journal
Electronics
Published
2025-03-02
DOI
https://doi.org/10.3390/electronics14051007
Citations
2
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
4.54
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Weak-PUF-Assisted Strong PUF with Inherent Security Using Metastability Implemented on FPGAs

Jiaji He, Gang Song, Qizhi Zhang, Yao Li et al.
2 citations
Electronics
Physical Unclonable Functions (PUFs) and Hardware Security
4.54
article

A Weak-PUF-Assisted Strong PUF with Inherent Security Using Metastability Implemented on FPGAs

Jiaji He, Gang Song, Qizhi Zhang, Yao Li, Yanjiang Liu, Xiaoxiang Wang, Yiqiang Zhao, Mao Ye
article en
2 citations

Abstract

Physical unclonable functions (PUFs) are emerging as highly promising lightweight hardware security primitives that offer novel information security solutions. PUFs capitalize on the intrinsic physical variations within circuits to generate unpredictable responses. Nevertheless, diverse PUF types often encounter difficulties in concurrently fulfilling multiple performance requisites. As is well known, strong PUFs possess significantly larger challenge–response pair (CRP) set sizes. However, they are vulnerable to machine learning (ML) attacks. Conversely, weak PUFs generate responses with superior randomness, yet their CRP sets are inadequate to satisfy the demands of practical applications. This paper presents a newly devised double-latch PUF (DL-PUF) to address this issue. This design significantly enhances both the CRP set size and security performance. The available CRPs of the DL-PUF design can reach up to 264, and its robust security features are also demonstrated in this paper. We have implemented this design on twelve 45 nm Xilinx Spartan 6 XC6SLX25 FPGAs. The experimental results indicate that our proposed DL-PUF performs well in terms of reliability, uniqueness, uniformity, and randomness. Additionally, three machine learning algorithms were employed to conduct comprehensive tests on the DL-PUF. The results reveal its excellent resilience against machine learning attacks.

ElectronicsVol. 14(5)
Tianjin University (CN), PLA Information Engineering University (CN)
Openalex Percentile: Top 8%
Physical Unclonable Functions (PUFs) and Hardware Security
4.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.