LAUSR

The cyber-security of the power grid is of extreme significance due to growing dependency on modern technologies. Several recent real-world incidents reveal the risk associated with false data injection attacks. Besides corrupting the sensor’s data, intruders can also target real-time dispatch signals (DS) sent to generation systems over an unsecured network to launch financially motivated attacks. To conduct the attacks, we construct a novel self-adaptive undetectable attack model, termed Imposter Attacks (IA). The devised IA adjusts its intensity based on system conditions allowing energy providers to unethically raise profit without impacting the grid stability. It is shown that by adopting IA, the infected DS remains undetectable by traditional detectors. Unlike existing attack models, the IA tend to hide the corrupted quantity among the normal system data making them extremely difficult to identify. The feasibility of the IA is studied on the Automatic Generation Control system of the IEEE-39 bus system.