Stackelberg Equilibria of an Anti-Jamming Game in Cooperative Cognitive Radio Networks
Bibliographic record
Abstract
The deceiving attacker is a radio jammer, equipped with a cognitive radio (CR) platform, which senses the frequency spectrum and launches jamming actions to block, mask, or emulate the legitimate active wireless connections. Using the IEEE 802.22 CR network (CRN) as a basis, this paper proposes a set of deception-based defense strategies to protect the CRNs from the deceiving attack. The Stackelberg framework is adopted in the formulation of the security problem to account for the attacker's reconnaissance capabilities. To this end, the Stackelberg equilibria between the attacker(s) and the defending CRs are calculated under the two cases when the attacker(s) and the defending CRs know and are uncertain about the primary user activity. The backward induction method is used to calculate the points of SE in the formulated security game. Both theoretical analysis and numerical results show that the defending CRs can decrease the probability of success of the deceiving attack to nearly 0% when the CRs have the incentive to defend the frequency channel(s).
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".