Large Language Model for Smart Inverter Cyber-Attack Detection via Textual Analysis of Volt/VAR Commands
This letter demonstrates a proof-of-concept validation of the Large Language Model (LLM) for smart inverter cyberattack detection through textual control commands. The proposed method can detect the manipulation of Volt/VAR curves and the comparison results with state-of-the-art machine learning techniques highlight its efficacy in identifying cyber attacks. Test results obtained from a real distribution feeder in Colorado, USA, validate the high accuracy for attack classification as well as demonstrate the potential of LLMs in adding a robust security layer for cyber-attacks.
Authors
- Junbo Zhao (ORCID: https://orcid.org/0000-0002-8498-9666)
- Alaa Selim (ORCID: https://orcid.org/0000-0002-5077-5168)
- Bo Yang (ORCID: https://orcid.org/0000-0001-8976-5971)
Institutions
- University of Connecticut (US)
- Hitachi Global Storage Technologies (United States) (US)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1109/tsg.2024.3453648
- Citations
- 18
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 6.30
Funders
- Office of Cybersecurity, Energy Security, and Emergency Response