Three Improved Algorithms for Multi-path Key Establishment in Sensor Networks Using Protocols for Secure Message Transmission.
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we propose a security model to capture active attacks against multi-path key establishment (MPKE) in sensor networks. Our model enhances previous models to capture more attacks and achieve essential security goals for multi-path key establishment. In this model, we can apply protocols for perfectly secure message transmission to solve the key establishment problem. We propose a new protocol for optimal one-round perfectly secure message transmission based on Reed-Solomon codes. Then we use this protocol to obtain two new multipath key establishment schemes that can be applied provided that fewer than one third of the paths contain an adversary node. Finally, we describe another MPKE scheme that tolerates a higher fraction (less than 1/2) of paths controlled by the adversary. This scheme is based on a new protocol for a weakened version of message transmission, which is very simple and efficient. Our multi-path key establishment schemes achieve improved security and lower communication complexity, as compared to previous schemes. 1
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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