Paper 2013/376
An Accurate Probabilistic Reliability Model for Silicon PUFs
Roel Maes
Abstract
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. An extensive experimental validation demonstrates that the new predicted distributions describe the empirically observed data statistics almost perfectly, even considering sensitivity to operational temperature. This allows studying PUF reliability behavior in full detail, including average and worst case probabilities, and is an invaluable tool for designing more efficient and better adapted PUFs and PUF-based systems.
Metadata
- Available format(s)
-
PDF
- Category
- Implementation
- Publication info
- Published elsewhere. Paper accepted to CHES 2013
- Keywords
- PUFsHardware SecurityFuzzy ExtractorKey GenerationReliability Model
- Contact author(s)
- roel maes @ intrinsic-id com
- History
- 2013-06-12: received
- Short URL
- https://ia.cr/2013/376
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2013/376,
author = {Roel Maes},
title = {An Accurate Probabilistic Reliability Model for Silicon {PUFs}},
howpublished = {Cryptology {ePrint} Archive, Paper 2013/376},
year = {2013},
url = {https://eprint.iacr.org/2013/376}
}
