BER-Based Physical Layer Security With Finite Codelength: Combining Strong Converse and Error Amplification
Why this work is in the frame
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Bibliographic record
Abstract
A bit-error-rate (BER)-based physical layer security approach is proposed for the finite blocklengths. For secure communication in the sense of high BER, the information-theoretic strong converse is combined with cryptographic error amplification achieved by the substitution permutation networks based on the confusion and diffusion. For the discrete memoryless channels (DMCs), an analytical framework is provided showing the tradeoffs among the finite blocklength, the maximum/minimum possible transmission rates, and the BER requirements for the legitimate receiver and the eavesdropper. In addition, the security gap is analytically studied for the Gaussian channels and the concept is extended to other DMCs including the binary symmetric channels and binary erasure channels.
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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 | 0.001 | 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