Silicon physical random functions
Proceedings of the 9th ACM conference on Computer and communications security
Physical unclonable functions for device authentication and secret key generation
Proceedings of the 44th annual Design Automation Conference
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
SIAM Journal on Computing
FPGA Intrinsic PUFs and Their Use for IP Protection
CHES '07 Proceedings of the 9th international workshop on Cryptographic Hardware and Embedded Systems
Efficient Helper Data Key Extractor on FPGAs
CHES '08 Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems
Low-Overhead Implementation of a Soft Decision Helper Data Algorithm for SRAM PUFs
CHES '09 Proceedings of the 11th International Workshop on Cryptographic Hardware and Embedded Systems
Soft decision helper data algorithm for SRAM PUFs
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Hardware intrinsic security from D flip-flops
Proceedings of the fifth ACM workshop on Scalable trusted computing
The glitch PUF: a new delay-PUF architecture exploiting glitch shapes
CHES'10 Proceedings of the 12th international conference on Cryptographic hardware and embedded systems
History mechanism supported differential evolution for chess evaluation function tuning
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Soft decision error correction for compact memory-based PUFs using a single enrollment
CHES'12 Proceedings of the 14th international conference on Cryptographic Hardware and Embedded Systems
CHES'12 Proceedings of the 14th international conference on Cryptographic Hardware and Embedded Systems
PUFKY: a fully functional PUF-based cryptographic key generator
CHES'12 Proceedings of the 14th international conference on Cryptographic Hardware and Embedded Systems
Bias-based modeling and entropy analysis of PUFs
Proceedings of the 3rd international workshop on Trustworthy embedded devices
Proceedings of the 3rd international workshop on Trustworthy embedded devices
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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 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.