Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition

Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition

Abstract Cyberattacks have given rise to several phenomena and have raised concerns among users and power system operators. When they are built to bypass state estimation bad data recognition methods executed in the conventional grid system control room, False Data Injection Attacks (FDIA) pose a si...

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Bibliographic Details
Main Authors: Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
False data injection attack
Cyberattack
Deep learning
Cetacean optimization Algorithm
Deep Belief Network
Online Access:https://doi.org/10.1038/s41598-024-82566-6
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https://doi.org/10.1038/s41598-024-82566-6

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