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Capacitance Sensor-Based Board-Level PUF for Device Identification

delete2025-01-01
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OA
AI
R
Rikuo Haga
A
Ayaki Tachikake
S
Shugo Kaji
D
Daisuke Fujimoto
Y
Yu‐ichi Hayashi
DOI:10.1109/ACCESS.2025.3606858delete
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Abstract

Abstract

En 中文
The proliferation of counterfeit and refurbished semiconductor devices has become a critical concern. Device identification techniques based on Physically Unclonable Functions (PUFs) have therefore attracted significant attention. Conventional PUFs exploit only die-internal process variations and thus cannot achieve board-level identification. In this work, we propose a novel method that also harnesses external process variations on the printed circuit board (PCB)—including trace geometry variations—to realize robust board-level device identification. Our method employs an on-chip capacitance sensor to measure the capacitance between signal traces and ground. A histogram of the sensor output values is generated, from which distinctive feature points in the distribution are extracted. By selecting bits that exhibit both high reproducibility and uniqueness, we construct a 30-bit device identifier. This approach eliminates the need for the large-scale measurement systems required by traditional techniques, enabling a more convenient yet high-precision identification process. Evaluation on 20 microcontroller boards demonstrates that the proposed method achieves 97.14% identification accuracy with the 30-bit identifier. The average normalized intra-device Hamming distance (Intra-HD) is 3.7%, and the average normalized inter-device Hamming distance (Inter-HD) is 46.7%, closely approximating ideal values. These results indicate that our technique offers a promising approach for ensuring board-level authenticity.
Keywords:
Physically unclonable function (PUF)
device identification
capacitance sensor
printed circuit board (PCB)
process variation
Hamming distance
authenticity assurance
counterfeit prevention

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

N
Nara Institute of Science and Technology
Scholars:
542
Papers: 188
Citations: 3.8K
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