The electrical power network is a critical infrastructure in today's society,so its safe and reliable operation is of major concern. State estimators arecommonly used in power networks, for example, to detect faulty equipment and tooptimally route power flows. The estimators are often located in controlcenters, to which large numbers of measurements are sent over unencryptedcommunication channels. Therefore cyber security for state estimators becomesan important issue. In this paper we analyze the cyber security of stateestimators in supervisory control and data acquisition (SCADA) for energymanagement systems (EMS) operating the power network. Current EMS stateestimation algorithms have bad data detection (BDD) schemes to detect outliersin the measurement data. Such schemes are based on high measurement redundancy.Although these methods may detect a set of basic cyber attacks, they may failin the presence of an intelligent attacker. We explore the latter byconsidering scenarios where stealthy deception attacks are performed by sendingfalse information to the control center. We begin by presenting a recentframework that characterizes the attack as an optimization problem with theobjective specified through a security metric and constraints corresponding tothe attack cost. The framework is used to conduct realistic experiments on astate-of-the-art SCADA EMS software for a power network example with 14substations, 27 buses, and 40 branches. The results indicate how stateestimators for power networks can be made more resilient to cyber securityattacks.
展开▼
