Abstract
The idea of using intrinsic random physical features to identify objects, systems, and people is not new. Fingerprint identification of humans dates at least back to the nineteenth century [21] and led to the field of biometrics. In the 1980s and 1990s of the twentieth century, random patterns in paper and optical tokens were used for unique identification of currency notes and strategic arms [2, 8, 53]. A formalization of this concept was introduced in the very beginning of the twenty-first century, first as physical one-way functions [41, 42], physical random functions [13], and finally as physical(ly) unclonable functions or PUFs.1 In the years following this introduction, an increasing number of new types of PUFs were proposed, with a tendency toward more integrated constructions. The practical relevance of PUFs for security applications was recognized from the start, with a special focus on the promising properties of physical unclonability and tamper evidence.
This work was supported by the IAP Program P6/26 BCRYPT of the Belgian State and by K.U. Leuven-BOF funding (OT/06/04). The first author’s research is funded by IWT-Vlaanderen under grant number 71369.
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Notes
- 1.
Note that there is a slight semantical difference between physical and physically unclonable functions. Further on in this work, we argue why the term physically unclonable is more fitting. For the remainder of this text, we will hence speak of PUFs as physically unclonable functions.
- 2.
Whenever not explicitly mentioned, a fixed environment is assumed.
- 3.
Possibly because they were proposed before the name PUF had been coined, or they were introduced in fields other than cryptographic hardware, where the notion of PUFs has not yet been introduced. When the name of a PUF in the section headings is between quotation marks, it means that we have introduced this name in this work for simplicity and easy reference.
- 4.
Note that we do not use the term silicon PUFs in this work. It has been used to describe (a class of) PUFs which can be implemented on silicon digital integrated circuits and use the intrinsic manufacturing variability in the production process as a source of randomness. As such, they can be considered a particular case of intrinsic PUFs.
- 5.
- 6.
By “\({{\mathsf{\Pi}}}_{{\ensuremath{\mathsf{\Gamma}}}} \neq {{\mathsf{\Pi}}}\)” here we mean that \({{\mathsf{\Pi}}}_{{\ensuremath{\mathsf{\Gamma}}}}\) and \({{\mathsf{\Pi}}}\) are (embedded in) physically distinct entities.
- 7.
A response containing n bits of entropy optimally allows for a unique identification in a population with an average size of \(2^\frac{n}{2}\) because of the birthday paradox.
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Maes, R., Verbauwhede, I. (2010). Physically Unclonable Functions: A Study on the State of the Art and Future Research Directions. In: Sadeghi, AR., Naccache, D. (eds) Towards Hardware-Intrinsic Security. Information Security and Cryptography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14452-3_1
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