A Survey of Security Challenges in Cognitive Radio Networks: Solutions and Future Research Directions
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
In this survey, we present a comprehensive list of major known security threats within a cognitive radio network (CRN) framework. We classify attack techniques based on the type of attacker, namely exogenous (external) attackers, intruding malicious nodes and greedy cognitive radios (CRs). We further discuss threats related to infrastructure-based CRNs as well as infrastructure-less networks. Besides the short-term effects of attacks over CRN performance, we also discuss the often ignored longer term behavioral changes that are enforced by such attacks via the learning capability of CRN. After elaborating on various attack strategies, we discuss potential solutions to combat those attacks. An overview of robust CR communications is also presented. We finally elaborate on future research directions pertinent to CRN security. We hope this survey paper can provide the insight and the roadmap for future research efforts in the emerging field of CRN security.
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 | 0.003 | 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