Enhanced hidden moving target defense in smart grids - Tian, Jue (2019)
Recent research has proposed a moving target defense (MTD) approach that actively changes transmission line susceptance to preclude stealthy false data injection (FDI) attacks against the state estimation of a smart grid. However, existing studies were often conducted under a weak adversarial setting, in that they ignore the possibility that alert attackers can also try to detect the activation of MTD before they launch the FDI attacks. We call this new threat as parameter confirming-first (PCF) FDI. To improve the stealthiness of MTD, we propose a hidden MTD approach that cannot be detected by the attackers and prove its equivalence to an MTD that maintains the power flows of the whole grid. Moreover, we analyze the completeness of MTD and show that any hidden MTD is incomplete in that FDI attacks may bypass the hidden MTD opportunistically. This result suggests that the stealthiness and completeness are two conflicting goals in MTD design. Finally, we propose an approach to enhancing the hidden MTD against a class of highly structured FDI attacks. We also discuss the MTD's operational costs under the dc and ac models. We conduct simulations to show the effectiveness of the hidden MTD against PCF-FDI attacks under realistic settings.