Anomaly Detection for GOOSE Spoofing Attacks in Digital Substations Using Deep Learning Models: A DNN and LSTM Approach

Anomaly Detection for GOOSE Spoofing Attacks in Digital Substations Using Deep Learning Models: A DNN and LSTM Approach

Digital substations have significantly increased the accuracy of power grid operations thus advancing high efficiency and reliability in grid operations. While this advancement has brought new cybersecurity challenges, in particular, for security of communication protocols such as Generic Object-Ori...

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Bibliographic Details
Main Authors: Trinal Fernando, Gowri Ramachandran, Mahinda Vilathgamuwa, Dhammika Jayalath
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Spoofing attacks
GOOSE protocol
digital substations
machine learning
deep learning
LSTM
Online Access:https://ieeexplore.ieee.org/document/11088114/
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