TY - GEN
T1 - Cyber security considerations on PMU-based state estimation
AU - Basumallik, Sagnik
AU - Eftekharnejad, Sara
AU - Davis, Nathan
AU - Nuthalapati, Nagarjuna
AU - Johnson, Brian K.
N1 - Funding Information:
This work is supported by the National Science Foundation (NSF) Grant No. 1600058.
Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/4/9
Y1 - 2018/4/9
N2 - State estimation allows continuous monitoring of a power system by estimating the power system state variables from measurement data. Unfortunately, the measurement data provided by the devices can serve as attack vectors for false data injection attacks. As more components are connected to the internet, power system is exposed to various known and unknown cyber threats. Previous investigations have shown that false data can be injected on data from traditional meters that bypasses bad data detection systems. This paper extends this investigation by giving an overview of cyber security threats to phasor measurement units, assessing the impact of false data injection on hybrid state estimators and suggesting security recommendations. Simulations are performed on IEEE-30 and 118 bus test systems.
AB - State estimation allows continuous monitoring of a power system by estimating the power system state variables from measurement data. Unfortunately, the measurement data provided by the devices can serve as attack vectors for false data injection attacks. As more components are connected to the internet, power system is exposed to various known and unknown cyber threats. Previous investigations have shown that false data can be injected on data from traditional meters that bypasses bad data detection systems. This paper extends this investigation by giving an overview of cyber security threats to phasor measurement units, assessing the impact of false data injection on hybrid state estimators and suggesting security recommendations. Simulations are performed on IEEE-30 and 118 bus test systems.
KW - Bad Data Detection
KW - False Data Injection
KW - Hybrid State Estimation
UR - http://www.scopus.com/inward/record.url?scp=85051732377&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051732377&partnerID=8YFLogxK
U2 - 10.1145/3212687.3212874
DO - 10.1145/3212687.3212874
M3 - Conference contribution
AN - SCOPUS:85051732377
SN - 9781450364065
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 5th Cybersecurity Symposium, CyberSec 2018
PB - Association for Computing Machinery
T2 - 5th Cybersecurity Symposium, CyberSec 2018
Y2 - 9 April 2018 through 11 April 2018
ER -