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
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.
Topics & Concepts
Risk analysis (engineering)Action (physics)Electric power systemComputer securityComputer sciencePower (physics)BusinessQuantum mechanicsPhysicsSmart Grid Security and ResiliencePower System Reliability and MaintenanceInfrastructure Resilience and Vulnerability Analysis