Line Failure Detection from PMU Data after a Joint Cyber-Physical Attack

The joint cyber and physical attacks propose new threats to many cyber-physical systems including smart grids. Due to the critical interdependency of power grids on the cyber components, modern power grids exhibit new vulnerabilities to cyber and physical attacks. In this paper, a joint cyber-physical attack is considered in which an adversary damages some lines physically (physical attack) and prevents the information flow from the attacked zone to the control center to tamper the observability of the grid and mask the physical failure (cyber attack). The goal of the presented work is to evaluate if the PMU data available from outside of the attacked zone can be used to estimate the state of the components in the attacked zone and how various scenarios of attacks will affect the state estimation. In this regard, a linear Minimum Mean Square Error (MMSE) estimation is applied to simulated PMU data. The MMSE is further extended to an iterative process with feedback to improve the performance of estimation. In this paper, the state estimation to recover the status of the components after the joint cyber physical attack is a data-driven approach and does not use system models. The IEEE 118 test case is used to show scenarios that the state of the lines can be estimated with minimum error as well as the lines that are difficult to estimate their state and thus may require more protection.