Build-in wiretap channel I with feedback and LDPC codes
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
A wiretap channel I is one of the channel models that was proved to achieve unconditional security. However, it has been an open problem in realizing such a channel model in a practical network environment. The paper is committed to solve the open problem by introducing a novel approach for building wiretap channel I in which the eavesdropper sees a binary symmetric channel (BSC) with error probability p while the main channel is error free. By taking advantage of the feedback and low density parity check (LDPC) codes, our scheme adds randomness to the feedback signals from the destination for keeping an eavesdropper ignorant; on the other hand, redundancy is added and encoded by the LDPC codes such that a legitimate receiver can correctly receive and decode the signals. With the proposed approach, unconditionally-secure communication can be achieved through interactive communications, in which the legitimate partner can realize the secret information transmission without a pre-shared secret key even if the eavesdropper has better channel from the beginning.
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) | 0.000 | 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 it