A Revision of the Quality Metrics of Physical Unclonable Functions

Physical unclonable functions (PUFs) leverage process variability to generate unique signatures in electronic devices. They are a strong alternative to conventional security mechanisms as they do not rely on non-volatile memories (NVMs) to store the secrets. However, PUFs can be influenced by external factors and may exhibit biased output distributions, leading to vulnerabilities that could compromise their uniqueness and resistance to cloning. The quality of a PUF is evaluated through a common set of metrics such as uniformity, bit-aliasing, uniqueness, and reliability. However, the lack of standardized methodologies hinders effective comparisons between diverse PUF designs, limiting the broader understanding of their performance. Besides, the underlying physics and mechanisms of PUFs makes them difficult to study and mitigate potential vulnerabilities and attacks. Overall, the quality metrics for PUFs are still evolving, and there is ongoing research to address these challenges and develop more robust and reliable PUFs. In this article, we demonstrate the limitations of current PUF evaluation metrics using experimental data and introduce a novel set of metrics that provide a more rigorous and comprehensive assessment.