A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication

Physical Unclonable Functions (PUFs) have emerged as a compelling solution for hardware-based authentication, yet arbiter PUFs often require additional mechanisms to address reliability challenges and vulnerabilities to attacks. In this paper, we propose a Pre-Selection-based Enhanced Arbiter PUF th...

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Main Authors: Rizka Reza Pahlevi, Hirokazu Hasegawa, Yukiko Yamaguchi, Hajime Shimada
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/11084796/
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author Rizka Reza Pahlevi
Hirokazu Hasegawa
Yukiko Yamaguchi
Hajime Shimada
author_facet Rizka Reza Pahlevi
Hirokazu Hasegawa
Yukiko Yamaguchi
Hajime Shimada
author_sort Rizka Reza Pahlevi
collection DOAJ
description Physical Unclonable Functions (PUFs) have emerged as a compelling solution for hardware-based authentication, yet arbiter PUFs often require additional mechanisms to address reliability challenges and vulnerabilities to attacks. In this paper, we propose a Pre-Selection-based Enhanced Arbiter PUF that filters noise-induced bit flips through repeated sampling without imposing substantial hardware overhead. We evaluate our design via a two-step methodology: an initial screening on a subset of boards, followed by a comprehensive assessment on 56 Field Programmable Gate Arrays (FPGA) boards—yielding 336 million challenge-response pairs (CRPs). Our findings indicate that the Pre-Selection process notably boosts reliability, with median values rising from about 72.63% up to 89.60% under higher sampling conditions. Even with a broader spread in uniqueness (majorly near the ideal value), most devices remain within a practically acceptable range for authentication. Crucially, False Acceptance Rate (FAR) and False Rejection Rate (FRR) stay below or near 2.5% in most configurations, underscoring the approach’s real-world viability. Additionally, bit aliasing reaches near-excellent levels, whereas Bit Error Rate (BER) remains below 0.2 or 0.3 for most boards. Entropy estimation consistently exceeds 95%, verifying that Pre-Selection retains the global randomness essential for security. A modeling attack test using Artificial Neural Network (ANN) model further yielded near-random prediction accuracy (ranging from 50% - 56%), confirming that enhanced reliability does not compromise unpredictability. These results suggest that a lightweight, modular post-processing scheme can balance reliability, distinctiveness, and randomness in arbiter PUFs, offering a scalable pathway to secure authentication in resource-constrained devices.
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spelling doaj-art-a247e1f117db4c8f93f929445aa9c2a62025-08-20T03:32:55ZengIEEEIEEE Access2169-35362025-01-011312752612754410.1109/ACCESS.2025.359047611084796A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based AuthenticationRizka Reza Pahlevi0https://orcid.org/0000-0002-4398-0251Hirokazu Hasegawa1Yukiko Yamaguchi2Hajime Shimada3Graduate School of Informatics, Nagoya University, Nagoya, JapanCenter for Strategic Cyber Resilience Research and Development, National Institute of Informatics, Tokyo, JapanInformation Technology Center, Nagoya University, Nagoya, JapanInformation Technology Center, Nagoya University, Nagoya, JapanPhysical Unclonable Functions (PUFs) have emerged as a compelling solution for hardware-based authentication, yet arbiter PUFs often require additional mechanisms to address reliability challenges and vulnerabilities to attacks. In this paper, we propose a Pre-Selection-based Enhanced Arbiter PUF that filters noise-induced bit flips through repeated sampling without imposing substantial hardware overhead. We evaluate our design via a two-step methodology: an initial screening on a subset of boards, followed by a comprehensive assessment on 56 Field Programmable Gate Arrays (FPGA) boards—yielding 336 million challenge-response pairs (CRPs). Our findings indicate that the Pre-Selection process notably boosts reliability, with median values rising from about 72.63% up to 89.60% under higher sampling conditions. Even with a broader spread in uniqueness (majorly near the ideal value), most devices remain within a practically acceptable range for authentication. Crucially, False Acceptance Rate (FAR) and False Rejection Rate (FRR) stay below or near 2.5% in most configurations, underscoring the approach’s real-world viability. Additionally, bit aliasing reaches near-excellent levels, whereas Bit Error Rate (BER) remains below 0.2 or 0.3 for most boards. Entropy estimation consistently exceeds 95%, verifying that Pre-Selection retains the global randomness essential for security. A modeling attack test using Artificial Neural Network (ANN) model further yielded near-random prediction accuracy (ranging from 50% - 56%), confirming that enhanced reliability does not compromise unpredictability. These results suggest that a lightweight, modular post-processing scheme can balance reliability, distinctiveness, and randomness in arbiter PUFs, offering a scalable pathway to secure authentication in resource-constrained devices.https://ieeexplore.ieee.org/document/11084796/Arbiter PUFauthenticationphysical unclonable functions (PUFs)pre-selection
spellingShingle Rizka Reza Pahlevi
Hirokazu Hasegawa
Yukiko Yamaguchi
Hajime Shimada
A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication
IEEE Access
Arbiter PUF
authentication
physical unclonable functions (PUFs)
pre-selection
title A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication
title_full A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication
title_fullStr A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication
title_full_unstemmed A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication
title_short A Pre-Selection–Enhanced Arbiter PUF for Strengthening PUF-Based Authentication
title_sort pre selection x2013 enhanced arbiter puf for strengthening puf based authentication
topic Arbiter PUF
authentication
physical unclonable functions (PUFs)
pre-selection
url https://ieeexplore.ieee.org/document/11084796/
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