Secure Lossy Transmission over Wiretap Channels with Side Information and State Information
Bibliographic record
Abstract
This paper investigates the problem of secure lossy transmission over wiretap channels with side information and state information. Aiming at the reliability and security of compressed pictures, videos and other files when they are transmitted, a wiretap channel model with side information and state information and a secure lossy source transmission scheme based on double binning technique under this model are proposed. By using Fano inequality and Csiszar sum identity, the inner bounds of transmission rate, distortion rate and information leakage rate are proved. Considering noisy situations in reality, the Gaussian noise channel under this model is analyzed concretely as an example. Based on error estimation and differential entropy theorem, the inner bounds of transmission rate and distortion rate are obtained. Moreover, the equivocation rate is introduced to transform the information leakage rate into the minimum mean square error of the estimated source and its outer bound is also obtained. The simulation results show that under the optimal conditions of the proposed system model, the transmission rate can reach 0.7315 bits/source bit, the distortion rate can reach 0.0052 bits/source bit and the information leakage rate can reach 0.1286 bits/source bit.
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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 | 0.003 |
| 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".