Distributed secure transmission for covert communication under multi‐user network
Bibliographic record
Abstract
Abstract In order to counter the double attack with wardens and eavesdroppers in the practical scenario, a distributed transmission scheme with security and covertness is proposed, which combines coding techniques and transmission protocol. The covert message is encoded by rateless codes and transmitted embedded in normal frames. The security is based on the random essence of rateless coding, and the covertness is achieved by ignoring the error frames and maintaining the signal waveform. The inter‐collusion between multiple wardens and eavesdroppers greatly increases the potential security hazards, which is first discussed in this paper. The authors can counter the inter‐collusion attack by adjusting the ratio of covert frame transmission in the distributed transmission scheme with security and covertness. Compared with the related work, this paper has many advantages, such as good robustness, lower extra complexity, and the insurance of the performance for both normal message and covert message. The analysis and simulation results show that our distributed transmission scheme with security and covertness can achieve both covertness and security based on the effective design under the existing communication system.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".