Secrecy Analysis in Wireless Network With Passive Eavesdroppers by Using Partial Cooperation
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a new location-based multicasting technique, for dual phase amplify-and-forward (AF) large networks, aiming to improve the security in the presence of non-colluding passive eavesdroppers. These eavesdroppers could also be part of this cooperative network as relays. In order to reduce the impact of these eavesdroppers on the network security, we propose a new transmission strategy where, for the first hop of each transmission time, while the destination is jamming, the source randomly chooses a different subset K of the total T relays, to transmit its message toward the destination. For practical implementation, sectoral transmission can be achieved with analog beamforming at the source's side. In the second hop, using the distributed beamforming technique, the K AF relays retransmit the received signal to the destination. We analytically demonstrated that the proposed technique decreases the probability of choosing the same sector that has certain eavesdroppers again, for each transmission time, to K/T. Moreover, we also show that the secrecy capacity scaling of our technique is still the same as for broadcasting. Hereafter, the lower and upper bounds of the secrecy outage probability are calculated, and it is shown that the security performance is remarkably enhanced, compared to conventional multicasting technique.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it