Overview
Smart grids integrate information and communication technology-enabled devices and Internet of Things technologies to facilitate the transition to decarbonization and electrification. However, these devices also introduce cybersecurity vulnerabilities. The false data injection (FDI) attack is one of the cyberattacks that cause severe consequences against smart grids. With the growing adoption of machine-learning-based cyberattack detectors in power systems, this session will assess the limitations of machine-learning detectors. The presenter will present a novel method for constructing highly stealthy false data injection attacks that bypass machine-learning detectors. Afterward, he will present the implementation of moving target defense in the physical layer of the power system to detect cyberattacks considering the cost, attack detection, and hiddenness.
Speaker Biography
Dr. Bo Liu is an Assistant Professor in the School of Engineering and Applied Science at Washington State University (WSU), Tri-cities, joined in August 2024. He received his Ph.D. from the Mike Wiegers Department of Electrical and Computer Engineering at Kansas State University, Manhattan, KS, USA, in 2021, where he also worked as a Postdoc and Research Assistant Professor. He has M.S. and B.S. degrees from Harbin Institute of Technology, China. In 2018 summer, he was a graduate research intern at the National Renewable Energy Laboratory (NREL). His primary research interests include cyber-physical security of power systems, machine learning applications, and state estimation in smart grids.