SAF-PUF: A Strong PUF with Zero-BER, ML-Resilience and Dynamic Key Concealment Enabled by RRAM Stuck-at-Faults

Targeting resource-constrained Internet of Things (IoT) devices, this paper proposes Stuck-at-Fault Physical Unclonable Function (SAF-PUF), a lightweight Resistive Random-Access Memory (RRAM)-based PUF that exploits the intrinsic addresses of manufacturing-induced SAF defects as a stable entropy source. By using the coordinates of Stuck-at-1 (SA1) cells to seed a 32-bit Linear Feedback Shift Register (LFSR), SAF-PUF generates robust, variable-length responses with zero Bit Error Rate (BER) across a wide temperature range from −40 °C to 125 °C, without any error-correction circuitry. Experimental results based on 100,000 Challenge–Response Pairs (CRPs) demonstrate strong resilience against machine learning (ML) attacks, with prediction accuracies of logistic regression (LR), support vector machines (SVM), neural networks (NN) and convolutional neural networks (CNNs) remaining close to 50%. Moreover, a “use-then-conceal” mechanism is introduced to enhance post-authentication security, enabling response obfuscation with minimal cell reconfiguration. These features make SAF-PUF a high-security, low-overhead hardware root of trust suitable for IoT applications.

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Publication Details

Journal
Applied Sciences
Published
2026-03-15
DOI
https://doi.org/10.3390/app16062817
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
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article

SAF-PUF: A Strong PUF with Zero-BER, ML-Resilience and Dynamic Key Concealment Enabled by RRAM Stuck-at-Faults

Applied Sciences
Physical Unclonable Functions (PUFs) and Hardware Security
article

SAF-PUF: A Strong PUF with Zero-BER, ML-Resilience and Dynamic Key Concealment Enabled by RRAM Stuck-at-Faults

article en

Abstract

Targeting resource-constrained Internet of Things (IoT) devices, this paper proposes Stuck-at-Fault Physical Unclonable Function (SAF-PUF), a lightweight Resistive Random-Access Memory (RRAM)-based PUF that exploits the intrinsic addresses of manufacturing-induced SAF defects as a stable entropy source. By using the coordinates of Stuck-at-1 (SA1) cells to seed a 32-bit Linear Feedback Shift Register (LFSR), SAF-PUF generates robust, variable-length responses with zero Bit Error Rate (BER) across a wide temperature range from −40 °C to 125 °C, without any error-correction circuitry. Experimental results based on 100,000 Challenge–Response Pairs (CRPs) demonstrate strong resilience against machine learning (ML) attacks, with prediction accuracies of logistic regression (LR), support vector machines (SVM), neural networks (NN) and convolutional neural networks (CNNs) remaining close to 50%. Moreover, a “use-then-conceal” mechanism is introduced to enhance post-authentication security, enabling response obfuscation with minimal cell reconfiguration. These features make SAF-PUF a high-security, low-overhead hardware root of trust suitable for IoT applications.

Applied SciencesVol. 16(6)
Shanghai Jiao Tong University (CN)
Openalex Percentile: Top 18%
Physical Unclonable Functions (PUFs) and Hardware Security
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