| Title | Sensor Scheduling-Based Detection of False Data Injection Attacks in Power System State Estimation |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Obata, Sho, Kobayashi, Koichi, Yamashita, Yuh |
| Conference Name | 2021 IEEE International Conference on Consumer Electronics (ICCE) |
| Date Published | jan |
| Keywords | composability, estimation error, False Data Detection, false data injection attacks, frequency estimation, Human Behavior, power networks, Power systems, pubcrawl, random sensor scheduling, resilience, Resiliency, Sensor systems, Sensors, state estimation, Steady-state, Switching frequency |
| Abstract | In state estimation of steady-state power networks, a cyber attack that cannot be detected from the residual (i.e., the estimation error) is called a false data injection attack. In this paper, to enforce security of power networks, we propose a method of detecting a false data injection attack. In the proposed method, a false data injection attack is detected by randomly choosing sensors used in state estimation. The effectiveness of the proposed method is presented by two numerical examples including the IEEE 14-bus system. |
| DOI | 10.1109/ICCE50685.2021.9427605 |
| Citation Key | obata_sensor_2021 |
Sensor Scheduling-Based Detection of False Data Injection Attacks in Power System State Estimation