Second-Order Asymptotics for One-way Secret Key Agreement
Bibliographic record
Abstract
Secret key agreement (SKA) is a basic cryptographic primitive that establishes a shared secret key between parties. In the two-party source model of SKA, Alice and Bob want to share a secret key. They each have private samples of two correlated variables that are partially leaked to Eve. In a one-way SKA protocol, Alice sends a single message to Bob over a public channel, allowing the two parties to calculate a shared secret key that will be essentially unknown to Eve. The length of the key is a function of the number of samples$n$. In this paper, we prove a tight second-order asymptotic approximation of the key length of one-way SKA protocols, and propose an approach to construct a computationally efficient one-way SKA protocol with near-optimum finite key length. We compare our results with related work, and discuss future research directions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.015 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".