Metraipolis › archive › dc_537fcc02ec2b

TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions — arXiv:2608.15391

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.15391
License (as archived): CC0-1.0
Archived: 2026-10-18T17:24:41.266Z
SHA-256 of the archived text: de574e3de723b590a7bb0964726ef46ab8f99c72502def0796294d30db0706f3
Stable URL of this page: https://metraipolis.com/documento/dc_537fcc02ec2b

How to cite

TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions — arXiv:2608.15391 — arXiv (en), https://arxiv.org/abs/2608.15391 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_537fcc02ec2b (Metraipolis archive dc_537fcc02ec2b, sha256 de574e3de723b590a7bb0964726ef46ab8f99c72502def0796294d30db0706f3)

BibTeX

@misc{dc537fcc02ec2b,
  title = {TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions — arXiv:2608.15391},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.15391},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_537fcc02ec2b; sha256 de574e3de723b590a7bb0964726ef46ab8f99c72502def0796294d30db0706f3},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.15391. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Large language model (LLM)-assisted energy-management tools can translate natural-language context into structured grid commands, but syntactic validity does not imply physical admissibility. This paper presents TwinGridShield, a model-independent runtime authorization layer that evaluates each proposed action in a deterministic network twin before release. The prototype checks connectivity, branch-flow, generator, and load-shedding invariants and records each decision in a hash-chained log. A controlled IEEE 14-bus study evaluates single-step switching, redispatch, and load-shedding actions using DC power flow and experimentally assigned branch ratings. In the matched-model experiment, a stochastic proposal source configured to select an unsafe action with probability p=0.84 produced 421 unsafe proposals in 500 attacked-condition trials, a realized rate of 84.2%. This value characterizes the configured surrogate and is not an empirical measurement of LLM prompt-injection susceptibility. TwinGridShield produced 0 unsafe releases in those 500 trials. Because action labeling and authorization used the same DC model, system state, branch ratings, and encoded constraints, this result verifies conformance of the implementation to its encoded authorization predicate rather than safety under model error. The principal robustness evaluation therefore introduces model mismatch. Unsafe acceptance reached 5.63% under bounded +20% and -20% per-bus load-measurement error and 30.09% when actual branch ratings were 20% below modeled ratings.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-18 in cs.AI).
Categorie arXiv: Artificial Intelligence (cs.AI) ; Cryptography and Security (cs.CR).
Pagina del lavoro: https://arxiv.org/abs/2608.15391 — 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 2026-10-18T16:29:13.796Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-18?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).