Denial of service attacks and mitigation for stability in cyber-enabled power grid
Bibliographic record
Abstract
Monitoring and actuation represent critical tasks for electric power utilities to maintain system stability and reliability. As such, the utility is highly dependent on a low latency communication infrastructure for receiving and transmitting measurement and control data to make accurate decisions. This dependency, however, can be exploited by an adversary to disrupt the integrity of the grid. We demonstrate that Denial of Service (DoS) attacks, even if perpetrated on a subset of cyber communication nodes, has the potential to succeed in disrupting the overall grid. One countermeasure to DoS attacks is enabling cyber elements to distributively reconfigure the system's routing topology so that malicious nodes are isolated. We propose a collaborative reputation-based topology configuration scheme and through game theoretic principles we prove that a low-latency Nash Equilibrium routing topology always exists for the system. Numerical results indicate that during an attack on a subset of cyber nodes, the proposed algorithm effectively enables the remaining nodes to converge quickly to an equilibrium topology and maintain dynamical stability in the specific instance of an islanded microgrid system.
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.
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 | 0.000 |
| 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 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".