Visible to the public False Data Injection Attacks Targeting DC Model-Based State Estimation

TitleFalse Data Injection Attacks Targeting DC Model-Based State Estimation
Publication TypeConference Paper
Year of Publication2017
AuthorsLiang, G., Weller, S. R., Zhao, J., Luo, F., Dong, Z. Y.
Conference Name2017 IEEE Power Energy Society General Meeting
Keywordsadversary, Adversary Models, attacking vector, cyber-attacks, DC model, economic operation, false data injection attack, grid operator, Human Behavior, Manganese, Meters, Metrics, Network topology, power engineering computing, power system security, power system state estimation, pre-specified meter target, pubcrawl, Q measurement, resilience, Resiliency, Scalability, secure operation, security of data, Smart grid, smart power grids, specific targets, state estimation, state variable target, Topology, Transmission line measurements

The false data injection attack (FDIA) is a form of cyber-attack capable of affecting the secure and economic operation of the smart grid. With DC model-based state estimation, this paper analyzes ways of constructing a successful attacking vector to fulfill specific targets, i.e., pre-specified state variable target and pre-specified meter target according to the adversary's willingness. The grid operator's historical reading experiences on meters are considered as a constraint for the adversary to avoid being detected. Also from the viewpoint of the adversary, we propose to take full advantage of the dual concept of the coefficients in the topology matrix to handle with the problem that the adversary has no access to some meters. Effectiveness of the proposed method is validated by numerical experiments on the IEEE-14 benchmark system.

Citation Keyliang_false_2017