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Improving awareness in early stages of security analysis: A zone partition method based on GrC

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Abstract

We present a method based on granular computing to support decision makers in analysing and protecting large-scale infrastructures or urban areas from external attacks by identifying a suitable partition of the infrastructure or the area under analysis. The method works on a very limited set of information relating to the vulnerabilities of components, and probability information regarding how vulnerabilities can impact meaningful partitions. These aspects make the method very useful as a reasoning mechanism to improve awareness and support rapid decision making at early stages of intelligence analysis, when information is scarce and contains a high degree of uncertainty. The results of the case study, which are based on the hypothesis of a terrorist attack on a subway, show that the method provides approximate solutions with the advantages of supporting reasoning at different levels of abstraction and providing simplicity of threat scenario analysis. We also discuss the limitations of the applicability of our approach.

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Notes

  1. In the following, we will use the terms “parts”, “zones”, or “regions” to refer in any case to parts of a partition.

  2. IEC 62443-3-2, http://isa99.isa.org/ISA99Wiki/WP-3-2.aspx

  3. https://www.ncpc.gov/topics/security/

  4. We can regard (1 − Er) as a level of defence or protection in a part pn. Of course, high levels of protection correspond to high values of Er and thus to low values of (1 − Er). In the following, when referring to level of protection, we will refer to (1 − Er).

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Authors and Affiliations

  1. Faculty of Software and Information Science, Iwate Prefectural University, Iwate, 020-8550, Japan

    Hamido Fujita

  2. Department of Information, Electric Engineering and Applied Mathematics and Department of Management and Innovation Systems, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, (SA), Italy

    Angelo Gaeta

  3. Department of Management and Innovation Systems, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, (SA), Italy

    Vincenzo Loia & Francesco Orciuoli

Authors
  1. Hamido Fujita
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  2. Angelo Gaeta
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  3. Vincenzo Loia
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  4. Francesco Orciuoli
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Correspondence to Hamido Fujita.

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Fujita, H., Gaeta, A., Loia, V. et al. Improving awareness in early stages of security analysis: A zone partition method based on GrC. Appl Intell 49, 1063–1077 (2019). https://doi.org/10.1007/s10489-018-1315-y

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