Data Security Defense: Modeling and Detection of Synchrophasor Data Spoofing Attack for Grid Edge
Journal Article
·
· Innovative Smart Grid Technologies (ISGT) (Online)
- Univ. of Tennessee, Knoxville, TN (United States)
- Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Data security and cyberattack have become critical issues in the distributed power system where adversaries can swap the source information of sensors or even spoof and alter measurements. However, the cyber security of the power system is challenged by the unpredictability and stealth of the spoofing attacks. Here, to protect the data security at the grid edge, this paper developed a synchrophasor data spoofing attack detection framework based on the time-frequency feature extraction techniques including the short-time Fourier transform (STFT) and object detection network for real-time synchrophasor data categorization and spoofing attack localization. The proposed approach outperforms earlier work in terms of spoofing attack detection and offers a vital localization function employing distributed synchrophasor sensors.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 2447242
- Journal Information:
- Innovative Smart Grid Technologies (ISGT) (Online), Journal Name: Innovative Smart Grid Technologies (ISGT) (Online) Vol. 2024; ISSN 2472-8152
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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