A Resilience Quantitative Framework for Wide Area Damping Control Against Cyberattacks
Bibliographic record
Abstract
This paper proposes a novel Stability-based Re-silience Metric (SRM) to evaluate the resilience of Wide-Area-Damping-Control (WADC) systems under different loading conditions. In the proposed method, the closest eigenvalue to the right half-plane in each loading condition is considered as an indicator to measure the distance from the instability condition. Moreover, the possible cyberattacks on Wide Area Network (WAN), resulting in full or partial Denial of Service (DoS), are also taken into consideration to measure how vulnerable the system is against cyberattacks. Attack tree and Common Vulnerability Scoring System (CVSS) are utilized to calculate the probability of attacks on multiple links. Finally, controllability and observability Gramians are employed to differentiate between attacks on different communication links. The efficiency of the proposed SRM is evaluated on the Kundur 2-area system, commonly used for inter-area stability studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".