Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values under Symmetric and Asymmetric Faults

Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values under Symmetric and Asymmetric Faults

10.1109/access.2021.3071141

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Bibliographic Details
Main Authors: Ustun, Taha Selim, Hussain, S. M. Suhail, Yavuz, Levent, Onen, Ahmet
Other Authors: DEPARTMENT OF COMPUTER SCIENCE
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
artificial intelligence
IEC 62351
IEEE 14-bus system
intrusion detection
renewable energy
Smartgrid cybersecurity
SV message security
Online Access:https://scholarbank.nus.edu.sg/handle/10635/232547
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Institution: National University of Singapore

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https://scholarbank.nus.edu.sg/handle/10635/232547

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