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Adversarially-Informed Node Criticality Identification in Power Grid Measurements — arXiv:2608.27393

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.27393
License (as archived): CC0-1.0
Archived: 2026-10-17T22:22:23.668Z
SHA-256 of the archived text: c69acee1f89a0adaa27e57cda574007c471ffaa397a6f17b4c7e9b0d03d5559f
Stable URL of this page: https://metraipolis.com/documento/dc_cd993cbefca1

How to cite

Adversarially-Informed Node Criticality Identification in Power Grid Measurements — arXiv:2608.27393 — arXiv (en), https://arxiv.org/abs/2608.27393 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_cd993cbefca1 (Metraipolis archive dc_cd993cbefca1, sha256 c69acee1f89a0adaa27e57cda574007c471ffaa397a6f17b4c7e9b0d03d5559f)

BibTeX

@misc{dccd993cbefca1,
  title = {Adversarially-Informed Node Criticality Identification in Power Grid Measurements — arXiv:2608.27393},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.27393},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_cd993cbefca1; sha256 c69acee1f89a0adaa27e57cda574007c471ffaa397a6f17b4c7e9b0d03d5559f},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.27393. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Power grid state estimation relies on sensor measurements that are increasingly vulnerable to adversarial corruption in cyberphysical environments, potentially leading to significant deviations in system observations. This motivates the need to identify critical measurement nodes whose compromise results in the most severe system-level impact. However, existing node criticality methods primarily rely on structural or steady-state analyses and do not explicitly account for adversarial effects on system behavior. To address this gap, this paper proposes an adversarially informed framework for identifying critical measurement nodes in linearized power systems. Within this framework, a structured attack generation mechanism is developed to construct stealthy and effective false data injection attacks (FDIAs) against an H-infinity resilient state estimator. Node criticality is then evaluated using coalition-based marginal contributions of compromised sensor subsets, estimated via permutation sampling over a prescribed set of admissible nodes, with the resulting importance scores mapped to the corresponding physical buses. Simulation results on the IEEE 14-bus system show that adversarially identified nodes induce larger deviations in frequency, voltage angle, and net power compared to randomly selected nodes, demonstrating the effectiveness of the proposed framework.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-08-28 in eess.SY).
Categorie arXiv: Systems and Control (eess.SY) ; Optimization and Control (math.OC).
Pagina del lavoro: https://arxiv.org/abs/2608.27393 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T22:17:01.668Z dalla pagina https://arxiv.org/catchup/eess.SY/2026-08-28?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).