Secret Key Capacity of Wiretapped Polytree-PIN
Bibliographic record
Abstract
In secret key agreement (SKA) in multiterminal channel model, terminals are connected by a noisy discrete memoryless channel (DMC) with multiple input and multiple outputs. Terminals can use the DMC to obtain correlated randomness, and communicate over a noiseless public channel to establish a shared secret key among a designated subset of terminals. We focus on a special class of multiterminal channel models, called wiretapped Polytree-PIN, in which the noisy channel consists of a set of independent point-to-point channels whose underlying undirected connectivity graph forms a tree. We consider a wiretap setting, where the output of each point-to-point channel is partially leaked to a passive wiretapper adversary, Eve, through a second independent noisy channel. A secure SKA protocol generates a group secret key such that Eve has no information about it. In this paper, we derive the wiretap secret key capacity, which is the largest achievable secret key rate, of the wiretapped PolytreePIN model. Our result also implies the key capacity of the non-wiretapped Polytree-PIN model, that is the case when there is no leakage from point-to-point channels to Eve.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".