Vulnerability Analysis and Consequences of False Data Injection Attack on Power System State Estimation

• Published in: IEEE transactions on power systems Vol. 31; no. 5; pp. 3864 - 3872
• Main Authors: Jingwen Liang, Sankar, Lalitha, Kosut, Oliver
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Constraining; Constraint modelling; Dynamical systems; Energy management; False data injection; Generators; Load modeling; Maximization; Optimization; Power flow; Power systems; State estimation; Topology; Transmission lines; vulnerability analysis
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2015.2504950

An unobservable false data injection (FDI) attack on AC state estimation (SE) is introduced and its consequences on the physical system are studied. With a focus on understanding the physical consequences of FDI attacks, a bi-level optimization problem is introduced whose objective is to maximize the physical line flows subsequent to an FDI attack on DC SE. The maximization is subject to constraints on both attacker resources (size of attack) and attack detection (limiting load shifts) as well as those required by DC optimal power flow (OPF) following SE. The resulting attacks are tested on a more realistic non-linear system model using AC state estimation and ACOPF, and it is shown that, with an appropriately chosen sub-network, the attacker can overload transmission lines with moderate shifts of load.