Towards Security Issues and Solutions in Cognitive Radio Networks
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
Cognitive radio technology is the vision of pervasive wireless communications that improves the spectrum utilization and offers many social and individual benefits. The objective of the cognitive radio network technology is to use the unutilized spectrum by primary users and fulfill the secondary users' demands irrespective of time and location (any time and any place). Due to their flexibility, the Cognitive Radio Networks (CRNs) are vulnerable to numerous threats and security problems that will affect the performance of the network. Little attention has been given to security aspects in cognitive radio networks. In this chapter, the authors discuss the security issues in cognitive radio networks, and then they present an intensive list of the main known security threats in CRN at various layers and the adverse effects on performance due to such threats, and the current existing paradigms to mitigate such issues and threats. Finally, the authors highlight proposed directions in order to make CRN more authenticated, reliable, and secure.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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