Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values under Symmetric and Asymmetric Faults
10.1109/access.2021.3071141
Saved in:
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: | |
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/232547 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Machine learning-based intrusion detection for achieving cybersecurity in smart grids using IEC 61850 GOOSE messages
by: Ustun, Taha Selim, et al.
Published: (2022) -
Calculation of the intrusion depth and its effects on microporous composite membranes
by: Chung, T.S.
Published: (2014) -
An Intrusion Response Decision-Making Model Based on Hierarchical Task Network Planning
by: MU, Chengpo, et al.
Published: (2010) -
Second-order continuous-time algorithm for optimal resource allocation in power systems
by: Wang, Dong, et al.
Published: (2021) -
Risk balance defense approach against intrusions for network server
by: MU, Chengpo, et al.
Published: (2013)