Security enhancement in cooperative jamming using compromised secrecy region minimization
Why this work is in the frame
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Bibliographic record
Abstract
A cooperative jamming system is investigated to enhance security of wireless communications in the presence of eavesdroppers. Different from traditional wireless security strategies that maximize secrecy capacity, a novel strategy based on the minimization of compromised secrecy region (CSR) is proposed. The secrecy region with a given secrecy outage probability is derived by considering path-loss and fading channel effects. Through numerical approximation of the outage probability, the optimal location and allocated power of the jammer are calculated to minimize the CSR which exhibits high secrecy outage probability. Without knowing the exact location of the randomly-distributed eavesdropper, our proposed scheme provides a new optimization criterion based on this compromised area minimization, thereby increasing the security level in cooperative jamming systems. Numerical results further validate the proposed CSR minimization scheme for cooperative jamming.
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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 | 0.000 | 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