A Stochastic Bayesian Game for Securing Secondary Frequency Control of Microgrids Against Spoofing Attacks With Incomplete Information
Bibliographic record
Abstract
While wireless communication has been implemented for the data exchange in the secondary frequency control of microgrids, the wireless links also open doors to spoofing attacks. Most existing game-theoretic approaches on securing control systems of microgrids against wireless spoofing attacks assume complete information. However, the defense scheme under perfect information assumption could lead to severe resource waste and significant detection delay due to the high over-defense rate. In this paper, we design a defense policy generation method for securing microgrids secondary frequency control facing spoofing attacks and incomplete observation. We formulate a multi-stage two-player stochastic Bayesian game (SBG) when the identity of the defender's opponent is uncertain. Furthermore, we propose a posterior identity belief update method, where Bayesian Nash equilibrium (NE) is considered to derive the boundary identity belief. Under the proposed SBG framework, an identity-dependent optimal defense scheme is obtained to simultaneously secure microgrids against potential spoofing attacks and reduce the over-defense rate. Comparison studies show that the proposed SBG-based defense policy can improve defense performance and significantly reduce over-defense rates.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".