Applying Large Language Models to Power Systems: Potential Security Threats

Jiaqi Ruan, Gaoqi Liang, Huan Zhao, Guolong Liu, Xianzhuo Sun, Jing Qiu, Zhao Xu, Fushuan Wen, Zhao Yang Dong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Applying large language models (LLMs) to modern power systems presents a promising avenue for enhancing decision-making and operational efficiency. However, this action may also incur potential security threats, which have not been fully recognized so far. To this end, this article analyzes potential threats incurred by applying LLMs to power systems, emphasizing the need for urgent research and development of countermeasures.

Original languageEnglish
Pages (from-to)3333-3336
Number of pages4
JournalIEEE Transactions on Smart Grid
Volume15
Issue number3
DOIs
Publication statusPublished - 1 May 2024

Keywords

  • large language models
  • Power systems
  • security threats

ASJC Scopus subject areas

  • General Computer Science

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