Event Details
Detecting False Data Injection Attacks on DC State Estimation
Presenter: Sami Gernaz
Supervisor:
Date: Mon, April 16, 2018
Time: 11:00:00 - 12:00:00
Place: EOW 430
ABSTRACT
ABSTRACT: Reliable state estimation is the key to ensuring stable operation of a power grid. An attacker may introduce malicious data into the power grid to manipulate sensor measurements. One of the most significant attacks that threatens the security of the power grid is a false data injection attack (FDIA). In order to detect such an attack, we propose an approach that employs a weighted least squares (WLS) state estimator and the Pearson correlation coefficient to determine whether an attack occurs. In this approach, the WLS estimates and the sensor measurements are compared using the Pearson correlation coefficient.
Results are presented which show that an FDIA can be accurately detected using this approach.