What question did this study set out to answer?

The aim is to design a PUF that enhances security and reliability against modeling attacks for authentication.

March 28, 2026Open Access

Reliable and Modeling-Attack-Resistant Feed-Forward Crossbar Matrix Arbiter PUF for Anti-Counterfeiting Authentication

Key Points

The aim is to design a PUF that enhances security and reliability against modeling attacks for authentication.
Design of a Feed-Forward Crossbar Matrix Arbiter PUF (FC-MA PUF)
Development of a selection mechanism for reliable challenge-response pairs
Implementation on a Field-Programmable Gate Array (FPGA)
Experimental evaluation using a training set of 1,000,000 challenge-response pairs
Achieved a bias of 49.88% and inter-chip uniqueness of 49.68%
Demonstrated a bit error rate (BER) of 0.018%
Stable CRP ratio decreased from 39.72% to 20.18% as feed-forward units increased from two to four
Prediction success rates for CMA-ES attack declined from 58.20% to 52.33% with increasing feed-forward units

Abstract

Physical Unclonable Functions (PUFs) represent a highly promising hardware security primitive, yet they face constraints of insufficient reliability and threats from modeling attacks. This paper designs a novel Feed-Forward Crossbar Matrix Arbiter PUF (FC-MA PUF). It incorporates an inter-stage crossbar structure, a feed-forward control system, and a mechanism for selecting reliable challenge-response pairs. These features significantly enhance the structural non-linearity and stability, substantially improving security and adaptability to a wider range of operating environments. It provides a high-strength authentication solution with low resource overhead for lightweight security-demanding devices such as IoT devices. The proposed FC-MA PUF has been successfully implemented on a Field-Programmable Gate Array (FPGA) platform. Experimental results for the selected 4-stage FC-MA PUF configuration show a bias, inter-chip uniqueness, and bit error rate (BER) of 49.88%, 49.68%, and 0.018%, respectively. Furthermore, the structure allows for flexible configuration of the number of feed-forward modules based on practical application requirements: a greater number of feed-forward modules enhances security but also leads to an increased BER and a decreased proportion of stable challenge-response pairs. Experimental results based on a training set of 1,000,000 challenge-response pairs demonstrate that: with two feed-forward units, the stable (Challenge Response Pair)CRP ratio is 39.72% and the Covariance Matrix Adaptation Evolutionary Strategies (CMA-ES) attack prediction success rate is 58.20%; with three units, the ratio decreases to 29.12% and the prediction rate drops to 54.91%; with four units, these values further decline to 20.18% and 52.33% respectively. These results confirm that the proposed FC-MA PUF effectively resists multiple modeling attacks, including Logistic Regression (LR), Support Vector Machine (SVM), and CMA-ES.

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Cite This Study

Yan et al. (Thu,) studied this question.

synapsesocial.com/papers/69c771dd8bbfbc51511e1ff2 https://doi.org/https://doi.org/10.3390/electronics15071375

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