Post-Quantum Cryptographic Schemes for Security Enhancement in 5G and B5G (Beyond 5G) Cellular Networks
Bibliographic record
Abstract
Abstract 5G is the fifth generation of broadband cellular network and beyond 5G can be the 6G, which will be the sixth generation of broadband cellular network. Even though studies about 5G are still evolving, 6G has become a hot topic for cellular researchers these days. The expansion in the field of 5G and 6G is still in infancy stage as many problems still need to be solved. Out of these, security of data transmission is a premier concern. Therefore, cybersecurity is becoming increasingly important for these cellular networks. This paper is focused upon providing the in-depth overview of 5G and B5G networks. The paper aims to evaluate the insights of the security services of 6G networks and outlines various data security techniques used by 5G networks. The paper also provides introduction to quantum computing for cryptography and evaluates various post-quantum cryptography techniques. Finally, some novel research trends and directions in correlation of security of 5G and beyond 5G networks are listed to guide further research in the area.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".