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Record W4391724773 · doi:10.14722/ndss.2024.24267

When Cryptography Needs a Hand: Practical Post-Quantum Authentication for V2V Communications

2024· article· en· W4391724773 on OpenAlexafffund
Geoff Twardokus, Nina Bindel, Hanif Rahbari, Sarah McCarthy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooPublic Works and Government Services CanadaNational Science Foundation
KeywordsComputer scienceCryptographyQuantum cryptographyAuthentication (law)Computer securityComputer networkPost-quantum cryptographyQuantumPublic-key cryptographyEncryptionPhysicsQuantum informationQuantum mechanics

Abstract

fetched live from OpenAlex

We tackle the atypical challenge of supporting postquantum cryptography (PQC) and its significant overhead in safety-critical vehicle-to-vehicle (V2V) communications, dealing with strict overhead and latency restrictions within the limited radio spectrum for V2V.For example, we show that the current use of spectrum to support signature verification in V2V makes it nearly impossible to adopt PQC.Accordingly, we propose a scheduling technique for message signing certificate transmissions (which we find are currently up to 93% redundant) that learns to adaptively reduce the use of radio spectrum.In combination, we design the first integration of PQC and V2V, which satisfies the above stringent constraints given the available spectrum.Specifically, we analyze the three PQ signature algorithms selected for standardization by NIST, as well as XMSS (RFC 8391), and propose a Partially Hybrid authentication protocol-a tailored fusion of classical cryptography and PQC-for use in the V2V ecosystem during the nascent transition period we outline towards fully PQ V2V.Our provably secure protocol efficiently balances security and performance, as demonstrated experimentally with software-defined radios (USRPs), commercial V2V devices, and road traffic and V2V simulators.We show our joint transmission scheduling optimization and Partially Hybrid design are scalable and reliable under realistic conditions, adding a negligible average delay (0.39 ms per message) against the current state-of-the-art.

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.

How this classification was reachedexpand

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.312

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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2024
Admission routes2
Has abstractyes

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