Silicon physical random functions
Proceedings of the 9th ACM conference on Computer and communications security
FPGA Intrinsic PUFs and Their Use for IP Protection
CHES '07 Proceedings of the 9th international workshop on Cryptographic Hardware and Embedded Systems
Physical unclonable function and true random number generator: a compact and scalable implementation
Proceedings of the 19th ACM Great Lakes symposium on VLSI
Extended abstract: The butterfly PUF protecting IP on every FPGA
HST '08 Proceedings of the 2008 IEEE International Workshop on Hardware-Oriented Security and Trust
Power-Up SRAM State as an Identifying Fingerprint and Source of True Random Numbers
IEEE Transactions on Computers
Context weighting for general finite-context sources
IEEE Transactions on Information Theory
The context-tree weighting method: basic properties
IEEE Transactions on Information Theory
Anti-counterfeiting with hardware intrinsic security
Proceedings of the Conference on Design, Automation and Test in Europe
DEMO: Inherent PUFs and secure PRNGs on commercial off-the-shelf microcontrollers
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Bias-based modeling and entropy analysis of PUFs
Proceedings of the 3rd international workshop on Trustworthy embedded devices
Secure PRNG seeding on commercial off-the-shelf microcontrollers
Proceedings of the 3rd international workshop on Trustworthy embedded devices
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An important building block for many cryptographic systems is a random number generator. Random numbers are required in these systems, because they are unpredictable for potential attackers. These random numbers can either be generated by a truly random physical source (that is non-deterministic) or using a deterministic algorithm. In practical applications where relatively large amounts of random bits are needed, it is also possible to combine both of these generator types. A non-deterministic random number generator is used to provide a truly random seed, which is used as input for a deterministic algorithm that generates a larger amount of (pseudo-)random bits. In cryptographic systems where Physical Unclonable Functions (PUFs) are used for authentication or secure key storage, an interesting source of randomness is readily available. Therefore, we propose the construction of a FIPS 140-3 compliant random bit generator based on an SRAM PUF in this paper. These PUFs are a source of instant randomness, which is available when powering an IC. Based on large sets of measurements, we derive the min-entropy of noise on the start-up patterns of SRAM memories. The min-entropy determines the compression factor of a conditioning algorithm, which is used to extract a truly random (256 bits) seed from the memory. Using several randomness tests we prove that the conditioned seed has all the properties of a truly random string with full entropy. This truly random seed can be derived in a low cost and area efficient manner from the standard IC component SRAM. Furthermore, an efficient implementation of a deterministic algorithm for generating (pseudo-)random output bits will be proposed. Combining these two functions leads to an ideal way to generate large amounts of random data based on non-deterministic randomness.