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National Science Foundation

Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

CPS-VO

dynamic invariant network

biblio

Visible to the public Detection of False Data Injection Attacks in Cyber-Physical Systems using Dynamic Invariants

Submitted by aekwall on Mon, 08/03/2020 - 10:29am
  • Power system dynamics
  • Kalman filters
  • learning (artificial intelligence)
  • Meters
  • Metrics
  • National security
  • power engineering computing
  • Power measurement
  • power system
  • Kalman filter
  • power system security
  • pubcrawl
  • Resiliency
  • robust estimation
  • Scalability
  • security of data
  • state estimation
  • traditional anomaly detection approaches
  • data-driven temporal causal relationships
  • adaptive filtering
  • adaptive robust thresholding
  • Anomaly Detection
  • bad data detection
  • Bayesian filtering
  • complex cyber-physical systems
  • cyber-physical systems
  • data-driven functional relationships
  • False Data Detection
  • dynamic invariant network
  • false data injection attack detection
  • false data injection attacks
  • G-KART
  • Granger causality based Kalman filter
  • graph theory
  • invariant graph
  • Jacobian matrices

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