Applying Large Language Models to Power Systems: Potential Security Threats
Fuente:
arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866909081017516032 |
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| author | Ruan, Jiaqi Liang, Gaoqi Zhao, Huan Liu, Guolong Sun, Xianzhuo Qiu, Jing Xu, Zhao Wen, Fushuan Dong, Zhao Yang |
| author_facet | Ruan, Jiaqi Liang, Gaoqi Zhao, Huan Liu, Guolong Sun, Xianzhuo Qiu, Jing Xu, Zhao Wen, Fushuan Dong, Zhao Yang |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_13361 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Applying Large Language Models to Power Systems: Potential Security Threats Ruan, Jiaqi Liang, Gaoqi Zhao, Huan Liu, Guolong Sun, Xianzhuo Qiu, Jing Xu, Zhao Wen, Fushuan Dong, Zhao Yang Artificial Intelligence Human-Computer Interaction Systems and Control 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. |
| title | Applying Large Language Models to Power Systems: Potential Security Threats |
| topic | Artificial Intelligence Human-Computer Interaction Systems and Control |
| url | https://arxiv.org/abs/2311.13361 |