Securing Cislunar Missions: A Location-Based Authentication Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As the evolution of next-generation communication networks proceeds, several wireless devices gain access to such networks, and the amount of transmitted data is rapidly increasing. Yet, with more and more critical data requiring confidential transmission and protection on the network, the security risks for wireless communications networks are even more significant. Considering the fixed-trajectory nature of satellites orbiting the Earth, it is worth investigating how this invariant can be leveraged to ensure security and reliability. In this paper, we propose a location-based authentication framework for cislunar space with distance verification to realize secure authentication. Expanding on this foundation, this study proposes tolerance variations based on relative orbital positions and noise sources in space. In addition, we performed Monte Carlo simulations under the assumption of noisy propagation conditions, providing a robust evaluation of the proposed framework’s performance in diverse and challenging lunar communication scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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