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Countermeasures Selection via Evidence Theory

(Short Paper)
  • Giusj Digioia
  • Chiara Foglietta
  • Gabriele Oliva
  • Stefano Panzieri
Conference paper
  • 1.9k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6983)

Abstract

In this paper an approach to understand the possible causes of outages in different and interconnected infrastructures, based on the evidences of detected failures is provided. Moreover, causes inferred are used to estimate possible not detected failures that, together with those detected, allow to better understand the infrastructure vulnerability and the impact of outages. Such a kind of analysis is regarded as a useful support to identify effective countermeasures, in order to mitigate risks related to malfunctioning behavior of critical infrastructures.

Keywords

Critical-Infrastructures Interdependency Modelling Evidence Theory Situation Awareness Risk Assessment 

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References

  1. 1.
    Endsley, M.: Toward a theory of situation awareness in dynamic systems: Situation awareness. Human Factors 37(1), 32–64 (1995)CrossRefGoogle Scholar
  2. 2.
    Digioia, G., Foglietta, C., Oliva, G., Panzieri, S., Setola, R.: Moving from looking to understanding: Situation awareness and prediction. In: Flammini, F., Setola, R., Franceschetti, G. (eds.) Effective Surveillance for Homeland Security: Balancing Technology and Social Issues, pp. 74–92. CRC Press/Taylor & Francis (2013)Google Scholar
  3. 3.
    Digioia, G., Foglietta, C., Oliva, G., Panzieri, S.: Aware on-line interdependency modeling via evidence theory. International Journal of Critical Infrastructures 9, 74–92 (2013)CrossRefGoogle Scholar
  4. 4.
    Dempster, A.: A Generalization of Bayesian Inference. In: Yager, R., Liu, L. (eds.) Classic Works of the Dempster-Shafer Theory of Belief Functions. STUDFUZZ, vol. 219, pp. 73–104. Springer, Heidelberg (2008), http://dx.doi.org/10.1007/978-3-540-44792-4_4 CrossRefGoogle Scholar
  5. 5.
    Smets, P.: Data Fusion in the Transferable Belief Model. In: Proceedings of the Third International Conference on Information Fusion, FUSION 2000, vol. 1, pp. PS21–PS33 (2000), http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=862713
  6. 6.
    Hall, D.L., Llinas, J.: Handbook of Multisensor Data Fusion. CRC Press (June 2001), http://www.worldcat.org/isbn/0849323797

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Giusj Digioia
    • 1
  • Chiara Foglietta
    • 1
  • Gabriele Oliva
    • 1
  • Stefano Panzieri
    • 1
  1. 1.Dipartimento di Informatica e AutomazioneUniversity “Roma TRE”RomaItaly

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