An Accurate Probabilistic Reliability Model for Silicon PUFs

The power of an accurate model for describing a physical process or designing a physical system is beyond doubt. The currently used reliability model for physically unclonable functions (PUFs) assumes an equally likely error for every evaluation of every PUF response bit. This limits an accurate description since experiments show that certain responses are more error-prone than others, but this fixed error rate model only captures average case behavior. We introduce a new PUF reliability model taking this observed heterogeneous nature of PUF cells into account. A substantial experimental validation demonstrates that the new predicted distributions describe the empirically observed data statistics almost perfectly, even considering sensitivity to operational temperature. This allows to study PUF failure behavior in full detail, including the average and the worst case probabilities. This is an invaluable tool for the future design of more efficient and better adapted PUFs and PUF-based systems.