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Data Security Defense: Modeling and Detection of Synchrophasor Data Spoofing Attack for Grid Edge

Journal Article · · Innovative Smart Grid Technologies (ISGT) (Online)
 [1];  [1];  [1];  [1];  [1];  [1];  [2]
  1. Univ. of Tennessee, Knoxville, TN (United States)
  2. 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

References (15)

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Detecting False Data Injection Attacks in Smart Grids: A Semi-Supervised Deep Learning Approach journal January 2021
Multifractal Characterization of Distribution Synchrophasors for Cybersecurity Defense of Smart Grids journal March 2022
Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach journal November 2022
Multiscale Adaptive Multifractal Detrended Fluctuation Analysis-Based Source Identification of Synchrophasor Data journal November 2022
Comparing YOLOv3, YOLOv4 and YOLOv5 for Autonomous Landing Spot Detection in Faulty UAVs journal January 2022

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