Data-Driven False Data-Injection Attack Design and Detection in Cyber-Physical Systems
Zhengen Zhao, Yimin Huang, Ziyang Zhen, Yuzhe Li
Abstract
In this article, a data-driven design scheme of undetectable false data-injection attacks against cyber-physical systems is proposed first, with the aid of the subspace identification technique. Then, the impacts of undetectable false data-injection attacks are evaluated by solving a constrained optimization problem, with the constraints of undetectability and energy limitation considered. Moreover, the detection of designed data-driven false data-injection attacks is investigated via the coding theory. Finally, the simulations on the model of a flight vehicle are illustrated to verify the effectiveness of the proposed methods.
Topics & Concepts
Subspace topologyComputer scienceCyber-physical systemCoding (social sciences)Identification (biology)Data miningScheme (mathematics)Artificial intelligenceStatisticsMathematicsMathematical analysisBotanyOperating systemBiologySmart Grid Security and ResilienceRadiation Effects in ElectronicsElectrostatic Discharge in Electronics