Advertisement

Analyzing Cascading Effects in Interdependent Critical Infrastructures

Conference paper
  • 139 Downloads
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 550)

Abstract

Critical Infrastructures (CIs) are resources that are essential for the performance of society, including its economy and its security. Large-scale disasters, whether natural or man-made, can have devastating primary (direct) effects on some CI and significant indirect effects (cascading effects) on other CIs, because CIs are interconnected and depend on each other’s services. Recent work by Laugé et al. expressed the dependency values among CIs as dependency matrices for various durations of the primary CI failure. For better preparedness and mitigation of CI failures knowledge of the weak points in CI interdependencies is crucial. To this effect, we have developed a MATLAB code that identifies the forward paths and loops between pairs of CIs based on a simplified version of Laugé’s matrices. The code calculates the parallel forward paths and loops dependencies to identify and quantify the amplification of cascading effects of any disruption that might hit one of the CIs included in the research. A main consequence, which has implications for expert assessment of dependencies between CIs, is that the cascading effects are not limited to the direct values expressed in the dependency matrices.

Keywords

Interdependent CIs Cascading effects Parallel forward paths effect Parallel loops effect Path dependency Loop dependency Expert assessment 

References

  1. 1.
    Norwegian Directorate for Civil Protection (DSB): Risikoanalyse av «Cyberangrep mot ekom-infrastruktur» (2015)Google Scholar
  2. 2.
    Ouyang, M.: Review on modeling and simulation of interdependent critical infrastructure systems. Reliab. Eng. Syst. Saf. 121, 43–60 (2014).  https://doi.org/10.1016/j.ress.2013.06.040CrossRefGoogle Scholar
  3. 3.
    Linstone, H.A., Turoff, M. (eds.): The Delphi method: techniques and applications. Addison-Wesley Pub. Co., Advanced Book Program, Reading (1975)zbMATHGoogle Scholar
  4. 4.
    Surowiecki, J.: The Wisdom of Crowds. Anchor Books, New York (2005)Google Scholar
  5. 5.
    Canzani, E.: Modeling dynamics of disruptive events for impact analysis in networked critical infrastructures. In: Tapia, A., Antunes, P., Bañuls, V.A., Moore, K., Porto, J. (eds.) ISCRAM 2016 Conference Proceedings – 13th International Conference on Information Systems for Crisis Response and Management. Federal University of Rio de Janeiro, Rio de Janeiro, Brasil (2016)Google Scholar
  6. 6.
    Abdelgawad, A.A., Farstad, T.-E., Gonzalez, J.J.: Vulnerability analysis of interdependent critical infrastructures upon a cyber-attack. In: Proceedings of the 52nd Hawaii International Conference on System Sciences., Hawaii, USA (2019)Google Scholar
  7. 7.
    Laugé, A.: Crisis Management Toolbox: the Relevant Role of Critical Infrastructures and their Dependencies (2014). http://hdl.handle.net/10171/37071
  8. 8.
    Laugé, A., Hernantes, J., Sarriegi, J.M.: Critical infrastructure dependencies: a holistic, dynamic and quantitative approach. Int. J. Crit. Infrastruct. Prot. 8, 16–23 (2015).  https://doi.org/10.1016/j.ijcip.2014.12.004CrossRefGoogle Scholar
  9. 9.
    European Commission: Green Paper on a European Programme for Critical Infrastructure Protection, COM (2005) 576 Final (2005). https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52005DC0576
  10. 10.
    Panula-Ontto, J.: EXIT method for cross-impact analysis. Unpublished (2016).  https://doi.org/10.13140/rg.2.2.17159.09121
  11. 11.
    Diestel, R.: Graph Theory. Springer-Verlag, Berlin Heidelberg (2017)CrossRefGoogle Scholar
  12. 12.
    Kreyszig, E.: Advanced Engineering Mathematics. Wiley, Hoboken (2011)zbMATHGoogle Scholar
  13. 13.
    Kuo, B.C.: Automatic Control Systems. John Wiley & Sons, New York (2003)Google Scholar
  14. 14.
    Ogata, K.: Modern Control Engineering. Pearson, Boston (2009)zbMATHGoogle Scholar
  15. 15.
    Chao, K.: A new look at the cross-impact matrix and its application in futures studies. J. Futur. Stud. 12, 45–52 (2008)Google Scholar
  16. 16.
    Bahar, M., Jantzen, J.: Digraph Toolbox - A Tutorial, Electric Power Engineering Department. Technical University of Denmark, Kgs. Lyngby (1994)Google Scholar
  17. 17.
    Abdelgawad, A.: Automated Eigenvalue analysis of SD models (2004)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Centre for Integrated Emergency ManagementUniversity of AgderGrimstadNorway
  2. 2.Faculty of Computers and InformationCairo UniversityGizaEgypt

Personalised recommendations