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Modeling and Mitigating Impact of False Data Injection Attacks on Automatic Generation Control
Rui Tan
, Hoang Hai Nguyen
, Eddy Y.S. Foo
, David K.Y. Yau
, Zbigniew Kalbarczyk
,
Ravishankar K. Iyer
, Hoay Beng Gooi
Coordinated Science Lab
Electrical and Computer Engineering
Information Trust Institute
Carl R. Woese Institute for Genomic Biology
National Center for Supercomputing Applications (NCSA)
Biomedical and Translational Sciences
Siebel School of Computing and Data Science
Center for Global Studies
Research output
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peer-review
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Keyphrases
Sensor Data
100%
Automatic Generation Control
100%
False Data Injection Attack
100%
Attack Impact
100%
Power Grid
66%
Remedial Actions
66%
Impact Model
66%
Optimal Attack Strategy
66%
Control System
33%
Impact Analysis
33%
Power System
33%
Simulation-based
33%
System Constants
33%
System Testing
33%
Sensor Measurement
33%
Nominal Value
33%
Attacker
33%
Blackout
33%
Equipment Damage
33%
Remaining Time
33%
Customer Loads
33%
Power System Model
33%
Physical Impacts
33%
Frequency Excursion
33%
Grid Frequency
33%
Engineering
Sensor Data
100%
Power Engineering
66%
Power Grid
66%
Data Link
66%
Control System
33%
Sensor Measurement
33%
Remaining Time
33%
Computer Science
Automatic Generation
100%
False Data Injection Attacks
100%
Efficient Algorithm
33%
Analysis Framework
33%
Attackers
33%
Sensor Measurement
33%
Remaining Time
33%
Mathematics
Power Grid
100%
Minimizes
50%
Control System
50%
Nominal Value
50%