GAKAP, multicast key agreement protocol for ad hoc networks based on group activity probability
Why this work is in the frame
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Bibliographic record
Abstract
We address the problem of multicast secure data over a multihop wireless ad hoc network. Many protocols that have been proposed are not really convenient for mobile ad hoc networks. We propose a group activity key agreement protocol (GAKAP) that aims to solve problems, such as mobility, unreliable links, and multihop communication cost, that are specific to ad hoc networks. The main idea is to focus on group dynamics and complete node mobility in the ad hoc environment to develop an adaptive protocol that is suitable for the network and group changes. Doing so, we extend and adapt the proposed tree based group Diffie-Hellman (TGDH) protocol to the pure mobile ad hoc network. We simulated our protocol over the Opnet environment under various mobility, group size, and group dynamic scenarios.
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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 | 0.001 | 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