Securing USIM-based Mobile Communications from Interoperation of SIMbased Communications
Bibliographic record
Abstract
Mobile networks security is constantly evolving and adapting to meet the needs of users and network operators.It is a requirement that there be interoperation of legacy security frameworks into modern mobile networks.Mobile networks originally had no real security which proved to be a deployment that was attacked constantly and the providers were defrauded of millions of dollars.To address the issues the SIM authentication protocols were developed to secure the resources of the network providers.The original SIM security framework developed in GSM networks had weaknesses brought about by the one way authentication protocol as well as weaknesses in the algorithms used to secure the communication.The evolution of authentication in mobile networks to address the problems in the SIM framework brought about the creation of the USIM protocols used in UMTS, LTE and WiMAX to secure the network from the SIM framework security issues.The integration of those two SIM and USIM frameworks brought forward the major weaknesses first found in the SIM framework.This paper proposes simple and effective solutions to reduce the possible attacks on the USIM protocols due to the above integration.First we propose a subtle modification to the SIM based GSM security protocols as a stand-alone solution, and then a modification to the USIM based UMTS security protocols is proposed as a second solution.Wireless communication allows for easy connectivity of devices without the expensive requirements of laying a physical network.One of the main difficulties in deploying wireless networks is the ability to secure information and resources on a medium that by its very nature broadcasts all information.A key aspect of securing wireless communication is the authentication protocol used to allow access to the network.The two major types of
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".