False Data Injection Attacks Against State Estimation

Abstract—A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measure-ments and power system models. Various techniques have been developed to detect and identify bad measurements, including the interacting bad measurements introduced by arbitrary, non-random causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers, since such malicious measurements can be considered as interacting bad measurements. In this paper, we present a new class of attacks, called false data injection attacks, against state estimation in electric power grids. We show that an attacker can take advantage of the configuration of a power system to launch such attacks to successfully bypass the existing techniques for bad measurement detection. Moreover, we look at two realistic attack scenarios, in which the attacker is either constrained to some specific meters (due to the physical protection of the meters), or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios, which can not only change the results of state estimation, but also modify the results in a predicted way. We demonstrate the success of these attacks through simulation using the IEEE 9-bus, 14-bus, 30-bus, 118-bus, and 300-bus systems. Our results indicate that security protection of the electric power grid must be revisited when there are potentially malicious attacks. I