Information-theoretic analysis of capacitive physical unclonable functions

Abstract

Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers)Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Physical unclonable functions ͑PUFs͒ can be used as a cost-effective means to store cryptographic key material in an unclonable way. In coating PUFs, keys are generated from capacitance measurements of a coating containing many randomly distributed particles with different dielectric constants. We introduce a physical model of coating PUFs by simplifying the capacitance sensors to a parallel plate geometry. We estimate the amount of information that can be extracted from the coating. We show that the inherent entropy is proportional to ͱ n͑log n͒ 3/2 , where n is the number of particles that fit between the capacitor plates in a straight line. However, measurement noise may severely reduce the amount of information that can actually be extracted in practice. In the noisy regime the number of extractable bits is, in fact, a decreasing function of n. We derive an optimal value for n as a function of the noise amplitude, the PUF geometry, and the dielectric constants.

Physically Unclonable Functions: A Study on the State of the Art and Future Research Directions

“…after an attack with a FIB the responses of the PUF are significantly changed. A more theoretical evaluation of coating PUFs was done in [55]. It was estimated that the entropy content of this PUF is approximately 6.6 bit per sensor.…”

PUFs: Myth, Fact or Busted? A Security Evaluation of Physically Unclonable Functions (PUFs) Cast in Silicon

“…The security properties of PUFs can either be evaluated theoretically, based on mathematical models of the underling physics [35,30], or experimentally by analyzing PUF implementations [10,34,8,9,16]. However, mathematical models never capture physical reality in its full extent, which means that the conclusions on PUF security drawn by this approach are naturally debatable.…”

Bias-based modeling and entropy analysis of PUFs

“…Extensive entropy analyses of optical PUFs by Tuyls et al [23] and of coating PUFs bySkorić et al [27] exist, but these analyses are not applicable to memory-based PUFs.…”