Securing the Authentication Process of LTE Base Stations
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
Securing sensitive information like the International Mobile Subscriber Identity has been a challenge on all generations of mobile telecommunication networks, i.e., 2G, 3G and 4G. In fact, many cases of compromising users' privacy in telecom networks have been reported such as the cases of rogue base stations capable of tracking, intercepting and collecting the sensitive data without the users' knowledge. To overcome these issues, we are proposing in this paper the use of a pre-shared key in the authentication process of Long-Term Evolution (LTE) base stations to local users. We are proposing a first hop authentication procedure to verify if the base station is legitimate by the User Equipment. We simulate our approach using the NetSim simulated environment to show how it is improving the data confidentiality in LTE networks.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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