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SRAM PUF Preselection Method Based on Neighboring Spatial Majority Voting
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AI
DOI：10.1007/s10836-025-06214-1.png)
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Abstract
En 中文
Static random access memory physically unclonable function (SRAM PUF) exploits process variations in identically designed transistors during production to generate a unique hardware fingerprint for each chip. The error correction construction cost of conventional SRAM PUF is high, and there is a problem of unstable response due to factors such as external ambient temperature or power supply voltage. Therefore, this paper uses the characteristics of spatial autocorrelation inside the SRAM circuit to propose a PUF preselection method based on neighboring spatial majority voting, and designs a generation scheme that can stably generate keys without improving the original circuit and increasing the test cost. Test data shows that in the case of 6.2% unstable SRAM cells, this method can obtain a 128-bit key with a failure rate of 2.1 x 10(-6) using 3200 SRAM cells. Under the change of power supply voltage (+/- 10%) and temperature (-20 degrees C similar to 70 degrees C), the bit error rate is still less than 3 x 10(-6). The results show that the method can meet the requirements of uniqueness and randomness of PUF key generation and has high stability.
Keywords:
SRAM PUF
Spatial majority voting
Spatial autocorrelation
Internet of things (IoT) security
Journal
J
IF:
1.3
Papers:
31
Citations:
549