Secrecy & Rate Adaptation for secure HARQ protocols
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.
Bibliographic record
Abstract
This paper is dedicated to the study of HARQ protocols under a secrecy constraint. An encoder sends information to a legitimate decoder while keeping it secret from the eavesdropper. Our objective is to provide a coding scheme that satisfies both reliability and confidentiality conditions. This problem has been investigated in the literature using a coding scheme that involves a unique secrecy parameter. The uniqueness of this parameter is sub-optimal for the throughput criteria and we propose a new coding scheme that introduces additional degrees of freedom. Our code involves Secrecy Adaptation and Rate Adaptation and we called it SARA-code. The first contribution is to prove that the SARA-code has small error probability and small information leakage rate. The second contribution is to show, over a numerical example, that the SARA-code improves the secrecy throughput.
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 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) | 0.001 | 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 it