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Graphon Neural Networks-Based Detection of False Data Injection Attacks in Dynamic Spatio-Temporal Power Systems

Cyberattacks on power systems have doubled due to digitization, impacting healthcare, social, and economic sectors. False data injection attacks (FDIAs) are a significant threat, allowing attackers to manipulate power measurements and transfer malicious data to control centers. In this paper, we pro...

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Principais autores: Rachad Atat, Abdulrahman Takiddin, Muhammad Ismail, Erchin Serpedin
Formato: Artigo
Idioma:Inglês
Publicado em: IEEE 2025-01-01
coleção:IEEE Open Access Journal of Power and Energy
Assuntos:
Power grids
graphon neural networks
attacks detection
transfer learning
dynamic graphs
Acesso em linha:https://ieeexplore.ieee.org/document/10843273/
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