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Record W2920823316 · doi:10.1109/isit.2019.8849553

Wiretap Secret Key Capacity of Tree-PIN

2019· article· en· W2920823316 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUpper and lower boundsTree (set theory)Key (lock)Computer scienceInformation leakageAdversaryRandom variableTheoretical computer scienceComputer networkMathematicsDiscrete mathematicsTopology (electrical circuits)CombinatoricsComputer securityStatistics

Abstract

fetched live from OpenAlex

Secret key agreement (SKA) is an essential primitive in cryptography and information security. In a multiterminal key agreement problem, there are a set of terminals each having access to a component of a vector random variable, and the goal of the terminals is to establish a shared key among a designated subset of terminals. This problem has been studied under different assumptions about the adversary. In the most general model, the adversary has access to a random variable Z, that is correlated with all terminals' variables. The single-letter characterization of the secret key capacity of this model, known as the wiretap secret key capacity, is not known for an arbitrary Z. In this paper, we calculate the wiretap secret key capacity of a Tree-PIN, when Z consists of noisy version of terminals' variables. We also derive an upper bound and a lower bound for the wiretap secret key capacity of a PIN, and prove their tightness for some special cases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.506

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 head0.013
GPT teacher head0.208
Teacher spread0.196 · 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