Combating channel eviction triggering denial‐of‐service attacks in cognitive radio networks
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Bibliographic record
Abstract
ABSTRACT We focus on a specific class of denial‐of‐service (DoS) attacks that is executed through Channel Eviction Triggering (CET), whereby adversary nodes unduly invoke mechanisms inherent in a cognitive radio (CR) network (CRN) operation to protect the licensed users and thus disrupt secondary access to the otherwise idle licensed bands. Skewing the spectrum sensing decision of CRN through sensing misreports is a manifestation of CET attacks. Whereas most studies in the literature focus on making the cooperative sensing more robust against such sensing misreports, we tackle the problem from the novel perspective of incentive alleviation. We distinguish two classes of such DoS attacks, which we refer to as CET and CET‐jamming attacks. In the former case, the incentive of adversary CRs is to remove the competition of truthful CRs in accessing the licensed spectral ranges. The latter class of DoS attack deals with scenarios in which the adversary nodes are mainly interested in denying the chances of communication of CRN over primary bands and as such their incentive cannot be modelled by the same utility maximisation model as truthful CRs. We propose a solution for each class of attacks, and our numerical results verify the effectiveness of the proposed CET defence scheme in both cases. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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