A Hierarchical Identity Based Key Management Scheme in Tactical Mobile Ad Hoc Networks
Why this work is in the frame
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Bibliographic record
Abstract
Hierarchical key management schemes would serve well for military applications where the organization of the network is already hierarchical in nature. Most of the existing key management schemes concentrate only on network structures and key allocation algorithms, ignoring attributes of the nodes themselves. Due to the distributed and dynamic nature of MANETs, it is possible to show that there is a security benefit to be attained when the node states are considered in the process of constructing a private key generator (PKG). In this paper, we propose a distributed hierarchical key management scheme in which nodes can get their keys updated either from their parent nodes or a threshold of sibling nodes. The dynamic node selection process is formulated as a stochastic problem and the proposed scheme can select the best nodes to be used as PKGs from all available ones considering their security conditions and energy states. Simulation results show that the proposed scheme can decrease network compromising probability and increase network lifetime in tactical MANETs.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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