• DocumentCode
    7008
  • Title

    Attack Detection and Identification in Cyber-Physical Systems

  • Author

    Pasqualetti, Fabio ; Dorfler, Florian ; Bullo, Francesco

  • Author_Institution
    Center for Control, Dynamical Syst., & Comput., Univ. of California at Santa Barbara, Santa Barbara, CA, USA
  • Volume
    58
  • Issue
    11
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    2715
  • Lastpage
    2729
  • Abstract
    Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial control processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper: (i) we propose a mathematical framework for cyber-physical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (ii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples.
  • Keywords
    fault diagnosis; graph theory; network theory (graphs); reliability theory; centralized attack detection monitor design; centralized attack identification monitor design; critical infrastructures; cyber-physical attacks; cyber-physical monitors; cyber-physical systems; distributed attack detection monitor design; distributed attack identification monitor design; external malicious attacks; failure analysis; graph theory; industrial control processes; mathematical framework; power systems; system theory; transportation networks; Biomedical monitoring; Control systems; Monitoring; Noise; Power system dynamics; Security; Sensors; Cyber-physical systems; descriptor systems; distributed control; fault detection; geometric control; graph theory; networks; security;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2013.2266831
  • Filename
    6545301