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Record W2465815659 · doi:10.1109/cjece.2016.2521877

A Ring Oscillator-Based PUF With Enhanced Challenge-Response Pairs

2016· article· en· W2465815659 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2016
Typearticle
Languageen
FieldComputer Science
TopicPhysical Unclonable Functions (PUFs) and Hardware Security
Canadian institutionsnot available
Fundersnot available
KeywordsRing oscillatorRandomnessPhysical unclonable functionComputer scienceAuthentication (law)Key (lock)Set (abstract data type)Ring (chemistry)Hardware security moduleState (computer science)Key generationEmbedded systemComputer engineeringTheoretical computer scienceCryptographyMathematicsAlgorithmElectronic engineeringComputer securityEngineeringChemistryStatistics

Abstract

fetched live from OpenAlex

Physical unclonable functions (PUFs) are powerful security primitives that provide cheap and secure solutions for security-related applications. Strong PUFs provide a large set of challenge-response pairs (CRPs) and are suitable for device authentication. Weak PUFs produce a small number of CRPs and can be used for key extraction. In this paper, we propose a novel method to enhance the CRP set of traditional ring oscillator-based PUFs (RO-PUFs). RO-PUFs are one of the most reliable types of PUFs and the best fit to implement on the field-programmable gate arrays. To the best of our knowledge, our method provides the maximum number of CRPs compared with the state of the art. In addition, the number of response bits that can be extracted by our method for each challenge is n-1 times more than the state of the art, where n is the number of ROs. The large number of response bits results in the authentication of more devices and generation of more keys. Evaluation of the PUF responses produced by applying our method shows a significant improvement in unpredictability and randomness compared with the related works. Moreover, we show that the responses are unique and reliable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.161
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it