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An Analysis of Cyclical Interdependencies in Critical Infrastructures

  • Nils Kalstad Svendsen
  • Stephen D. Wolthusen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5141)

Abstract

In this paper we discuss the properties and algorithmic methods for the identification and classification of cyclical interdependencies in critical infrastructures based on a multigraph model of infrastructure elements with a view to analyze the behavior of interconnected infrastructures under attack. The underlying graph model accommodates distinct types of infrastructures including unbuffered classes such as telecommunications and buffered structures such as oil and gas pipelines. For interdependency analyzes particularly between different infrastructure types, cycles multiple crossing infrastructure sector boundaries are still relatively poorly understood, and their dynamic properties and impact on the availability and survivability of the overall infrastructure is of considerable interest. We therefore propose a number of algorithms for characterizing such cyclical interdependencies and to identify key characteristics of the cycles such as the strength of the dependency or possible feedback loops and nested cycles which can be of particular interest in the development of mitigation mechanisms.

Keywords

Multigraph models interdependency analysis multiflow models 

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References

  1. 1.
    Svendsen, N.K., Wolthusen, S.D.: Multigraph Dependency Models for Heterogeneous Infrastructures. In: First Annual IFIP Working Group 11.10 International Conference on Critical Infrastructure Protection, Hanover, NH, USA, IFIP, pp. 117–130. Springer, Heidelberg (2007)Google Scholar
  2. 2.
    Svendsen, N.K., Wolthusen, S.D.: Connectivity models of interdependency in mixed-type critical infrastructure networks. Information Security Technical Report 12(1), 44–55 (2007)CrossRefGoogle Scholar
  3. 3.
    Svendsen, N.K., Wolthusen, S.D.: Analysis and Statistical Properties of Critical Infrastructure Interdependency Multiflow Models. In: Proceedings from the Seventh Annual IEEE SMC Information Assurance Workshop, United States Military Academy, West Point, NY, USA, jun 2007, pp. 247–254. IEEE Press, Los Alamitos (2007)CrossRefGoogle Scholar
  4. 4.
    Karmarkar, N.: A New Polynomial Time Algorithm for Linear Programming. Combinatorica 4(4), 373–395 (1984)CrossRefMathSciNetzbMATHGoogle Scholar
  5. 5.
    Schrijver, A.: Combinatorial Optimization, vol. 3. Springer, Heidelberg (2003)zbMATHGoogle Scholar
  6. 6.
    Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to Algorihms, 1st edn. The MIT Electrical Engineering and Computer Science Series. MIT Press, Cambridge (1990)Google Scholar
  7. 7.
    Brandes, U., Erlebach, T. (eds.): Network Analysis. LNCS, vol. 3418. Springer, Heidelberg (2005)zbMATHGoogle Scholar
  8. 8.
    Wolthusen, S.: Modeling Critical Infrastructure Requirements. In: Proceedings from the Fifth Annual IEEE SMC Information Assurance Workshop, United States Military Academy, West Point, NY, USA, pp. 258–265. IEEE Press, Los Alamitos (2004)Google Scholar
  9. 9.
    Bologna, S., Di Costanzo, G., Luiijf, E., Setola, R.: An Overview of R&D Activities in Europe on Critical Information Infrastructure Protection (CIIP). In: López, J. (ed.) CRITIS 2006. LNCS, vol. 4347, pp. 91–102. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Mauw, S., Oostdijk, M.: Foundations of Attack Trees. In: Won, D., Kim, S. (eds.) ICISC 2005. LNCS, vol. 3935, pp. 186–198. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Baiardi, F., Suin, S., Telmon, C., Pioli, M.: Assessing the Risk of an Information Infrastructure Through Security Dependencies. In: Lopez, J. (ed.) CRITIS 2006. LNCS, vol. 4347, pp. 42–54. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Callaway, D.S., Newman, M.E.J., Strogatz, S.H., Watts, D.J.: Network Robustness and Fragility: Percolation on Random Graphs. Physical Review Letters 85(25), 5468–5471 (2000)CrossRefGoogle Scholar
  13. 13.
    Cohen, R., Erez, K., ben-Avraham, D., Havlin, S.: Resilience of the Internet to Random Breakdowns. Physical Review Letters 85(21), 4626–4628 (2000)CrossRefGoogle Scholar
  14. 14.
    Cohen, R., Erez, K., ben-Avraham, D., Havlin, S.: Breakdown of the Internet under Intentional Attack. Physical Review Letters 86(16), 3682–3685 (2001)CrossRefGoogle Scholar
  15. 15.
    Dorogovtsev, S.N., Mendes, J.F.F.: Effect of the accelerating growth of communications networks on their structure. Physical Review E 63, 025101 (2001)CrossRefGoogle Scholar
  16. 16.
    Casselman, W.: Networks. Notices of the American Mathematical Society 51(4), 392–393 (2004)MathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Nils Kalstad Svendsen
    • 1
  • Stephen D. Wolthusen
    • 1
    • 2
  1. 1.Norwegian Information Security LaboratoryGjøvik University CollegeGjøvikNorway
  2. 2.Information Security Group, Department of Mathematics, Royal HollowayUniversity of LondonEghamUK

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