TY - GEN
T1 - Simulation Based Modeling for a Cybersecure Power Grid
AU - Mesham, Michael
AU - Fahmy, Mahmoud
AU - Celik, Nurcin
N1 - Publisher Copyright:
© 2020 SCS.
PY - 2020/5
Y1 - 2020/5
N2 - The North American bulk power system is one of the most vital infrastructures in modern society as it accounts for virtually all the electricity supplied to the United States, Canada, and a portion of Baja Notre California, Mexico. Cyberattacks, of all forms, are becoming increasingly prominent within power networks and other infrastructures whereas their resolution can consume a significant deal of time and monetary resources. This can be further worsened if there are subsequent physical attacks in the wake of a cyberattack, as the system downtime leaves the government, military, and other critical infrastructures incredibly vulnerable This research aims to investigate if different patterns of cyberattacks could be identified with speed using simulation and machine learning algorithms. More specifically, we design a simulation model that can help better defend against cyber threats.
AB - The North American bulk power system is one of the most vital infrastructures in modern society as it accounts for virtually all the electricity supplied to the United States, Canada, and a portion of Baja Notre California, Mexico. Cyberattacks, of all forms, are becoming increasingly prominent within power networks and other infrastructures whereas their resolution can consume a significant deal of time and monetary resources. This can be further worsened if there are subsequent physical attacks in the wake of a cyberattack, as the system downtime leaves the government, military, and other critical infrastructures incredibly vulnerable This research aims to investigate if different patterns of cyberattacks could be identified with speed using simulation and machine learning algorithms. More specifically, we design a simulation model that can help better defend against cyber threats.
KW - North American bulk power system
KW - cybersecurity
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85092047707&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85092047707&partnerID=8YFLogxK
U2 - 10.22360/SpringSim.2020.CSE.006
DO - 10.22360/SpringSim.2020.CSE.006
M3 - Conference contribution
AN - SCOPUS:85092047707
T3 - Proceedings of the 2020 Spring Simulation Conference, SpringSim 2020
BT - Proceedings of the 2020 Spring Simulation Conference, SpringSim 2020
A2 - Barros, Fernando J.
A2 - Hu, Xiaolin
A2 - Kavak, Hamdi
A2 - Del Barrio, Alberto A.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Spring Simulation Conference, SpringSim 2020
Y2 - 18 May 2020 through 21 May 2020
ER -