APUF Faults: Impact, Testing, and Diagnosis
Yeqi Weia, Tim Foxb, Vincent Dumoulinc, Wenjing Raod and Natasha Devroyee
Department of Electrical and Computer Engineering University of Illinois Chicago, Chicago, IL 60607, USA
aywei30@uic.edu
btfox8@uic.edu
cvdumou2@uic.edu
dwenjing@uic.edu
edevroye@uic.edu
ABSTRACT
Arbiter Physically Unclonable Functions (APUFs) are hardware security primitives that exploit manufacturing randomness to generate unique digital fingerprints for ICs. This paper theoretically and numerically examines the impact of faults native to APUFs – mask parameter faults from the design phase, or process variation (PV) during the manufacturing phase. We model them statistically, and explain quantitatively how these faults affect the resulting APUF bias and uniqueness. On a single APUF instance, these faults manifest as some outlier delta elements in magnitude, thus we focus on such abnormal delta elements when addressing APUF faults. To detect such bad APUF instances and diagnose the abnormal delta elements, we propose a testing methodology which partitions a random set of challenges so that a specific delta element can be targeted, forming a perceivable bias in the responses over these sets. This low-cost approach is highly effective in detecting and diagnosing bad APUFs with abnormal delta element(s).
Keywords: Arbiter Puf, Arbiter Puf Faults, Testing, Diagnosis.
