False Data Injection Attacks against State Estimation in the Smart Grid.

The integration of Information and Communication Technology (ICT) in Electric Power Systems (EPS) enhances monitoring and control, with critical infrastructures like SCADA and Wide Area Monitoring Systems (WAMSs) playing a key role in grid security. State Estimation (SE) ensures system awareness, supported by synchrophasors such as Phasor Measurement Units (PMUs) for monitoring. However, attackers exploit ICT vulnerabilities to manipulate PMU measurements, misleading SE and triggering incorrect control actions. Therefore, we analyze the detection performance of residual-based detection, Cumulative Sum (CUSUM) for change point detection, and Kullback-Leibler divergence (KLD) for distribution-based analysis and demonstrate their effectiveness in preserving state estimation integrity.