APUF Faults: Testing, Diagnosing, and Salvaging

Arbiter Physically Unclonable Functions (APUFs) are hardware security primitives that generate unique digital fingerprints for integrated circuits (ICs) by exploiting manufacturing randomness. Ideally, a good APUF production line is characterized by symmetry, or equal delay for each track pair from the mask, and uniform, unskewed PV for all of the stages of all APUFs. 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 APUF response bias and uniqueness. We propose simple and efficient testing methodologies for faults in the APUF production line. The number of APUFs with positive responses (called the response bias) is used for the detection of the mask-phase fault, while the number of APUFs with the same response is used for the detection of the PV-phase fault. On a single APUF instance, these faults manifest as outlier delta elements in magnitude. To detect such faulty APUF instances and diagnose the abnormal delta elements, we propose a testing methodology that 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). Instead of discarding these unqualified APUFs, our work proposes to use challenge selection to mitigate the undesired fault impacts. We present a systematic challenge selection-based salvaging strategy where faults ``cancel'' each other, such that the response bias and uniqueness are as close to ideal as possible. This is achieved based on a method to estimate the intensity of each faulty element for an APUF batch with many $\mu$-faults, and the estimated result is valid for salvaging APUFs generated from this $\mu$-fault production line. The presented strategies are low-cost (which means they need only a small number of APUF samples, no extra hardware), effective, and applicable to multiple faults.