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