Identifying the Attack Probability of Measurements in Nonlinear State Estimator

Measuring devices are the basic building block for real-time monitoring of the cyber-physical power system. Any cyber-attack on these measuring infrastructures may impair the overall operation and control of the power grid. Therefore, when evaluating the cybersecurity of cyber-physical power systems, identifying the cyber risk associated with these devices presents a significant challenge. For this reason, this paper investigates the quantitative evaluation of cyber risk associated with the various measuring devices in the system. A probabilistic approach is proposed in this work to identify the attack probabilities of various field measurements, using a combinatorial model. These attack probabilities are needed to help the system operator comprehend the cyber risk associated with different AMI/IEDs measurements. For two different attack scenarios, numerical simulations were carried out on IEEE 118–bus test system to demonstrate the attack probabilities of the different measuring devices.