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Record W4220946875 · doi:10.1145/3517341

Authenticity, Integrity, and Replay Protection in Quantum Data Communications and Networking

2022· article· en· W4220946875 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACM Transactions on Quantum Computing · 2022
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceQuantum cryptographyQuantum networkQuantum teleportationQuantum information scienceQuantum channelQuantum entanglementData integrityQuantumComputer networkTheoretical computer scienceQuantum informationComputer securityPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Quantum data communications and networking involve classical hardware and software. Quantum storage is sensitive to environmental disturbances that may have malicious origins. Teleportation and entanglement swapping, two building blocks for the future quantum Internet, rely on secure classical bit communications. When lack of authenticity, integrity, and replay protection may have a high impact, quantum data communications are at risk and need to be protected. Building upon quantum cryptography and random generation of quantum operators, we propose a solution to protect the authenticity, integrity, and replay of quantum data communications. Our solution includes a classical data interface to quantum data cryptography. We describe how classical keying material can be mapped to quantum operators. This enables classical key management techniques for secure quantum data communications.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.002
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 head0.075
GPT teacher head0.301
Teacher spread0.227 · 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