Fusion of Bayesian and Ontology Approach Applied to Decision Support System for Critical Infrastructures Protection

  • Rafał Kozik
  • Michał Choraś
  • Witold Hołubowicz
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 45)


In this paper, a decision support system based on the ontology knowledge for Critical Infrastructure security assessment is presented. The ontology provides vulnerabilities, threats and safeguards classification and their relationships with other security aspects. Such knowledge is used to build Bayesian network, which is used to asses the severity level of the detected threats. Described approach is applied in decision support tool developed within the INSPIRE project aiming at increasing security and protection through infrastructure resilience. The major contribution of this paper is the fusion of the ontology and Bayesian approach utilized in the reasoning engine of the decision support application.


Bayesian Network Decision Support System Inference Engine Critical Infrastructure Ontology Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    European Parliament legislative resolution of 10 July 2007, on the proposal for a Council directive on the identification and designation of European Critical Infrastructure and the assessment of the need to improve their protection (COM(2006)0787 C6-0053/2007 2006/0276(CNS)) (July 2007)Google Scholar
  2. 2.
    XiaoFeng, D., YuJiong, G., Kun, Y.: Study on Intelligent Maintenance Decision Support System Using for Power Plant Equipment. In: Proc. of the IEEE International Conference on Automation and Logistics Qingdao, China, 96100 (September 2008)Google Scholar
  3. 3.
    Lee, S.J., Mo, K., Seong, P.H.: Development of an Integrated Decision Support System to Aid the Cognitive Activities of Operators in Main Control Rooms of Nuclear Power Plants. In: Proc. of IEEE Symposium on Computational Intelligence in Multicriteria Decision Making (MCDM), pp. 146–152 (2007)Google Scholar
  4. 4.
    Zhang, B., Wu, G., Shang, S.: Research on Decision Support System of Water Pollution Control Based On Immune Agent. In: Proc. of International Symposium on Computer Science and Computational Technology, ISCSCT, vol. 1, pp. 114–117 (2008)Google Scholar
  5. 5.
    Xie, L., Wang, Z., Bian, L.: The Research of Oileld Flood Precaution Decision Support System. In: Proc. of International Seminar on Business and Information Management, ISBIM 2008, vol. 2, pp. 236–239 (December 2008)Google Scholar
  6. 6.
    ISO/IEC 13335-1:2004, Information Technology Security Techniques Management of information and communications technology security Part 1: Concepts and models for information and communications technology security management (2004)Google Scholar
  7. 7.
    Choras, M., Stachowicz, A., Kozik, R., Flizikowski, A., Renk, R.: Ontology-based approach to SCADA systems vulnerabilities representation for CIP. Electronics 11, 35–38 (2009)Google Scholar
  8. 8.
    Choras, M., Flizikowski, A., Kozik, R., Renk, R., Holubowicz, W.: Ontology-Based Reasoning Combined with Inference Engine for SCADA-ICT Interdependencies, Vulnerabilities and Threats Analysis. In: Pre-Proc. of 4th International Workshop on Critical Information Infrastructures Security, CRITIS 2009, Bonn, Germany, pp. 203–214. Fraunhofer IAIS (2009)Google Scholar
  9. 9.
    SWRL: A Semantic Web Rule Language Combning OWL and RuleML, W3C Member Submission,
  10. 10.
    Deliverable D2.3, Ontological approach and inference engine, INSPIRE Project (2009)Google Scholar
  11. 11.
    Macaulay, T.: Critical infrastructure: Understanding Its Component Parts, Vulnerabilities, Operating Risks, and Interdependencies (August 2008)Google Scholar
  12. 12.
    Lewis, T.G.: Critical Infrastructure Protection in Homeland Security: Defending a Networked Nation. Wiley-Interscience, Hoboken (2006)CrossRefGoogle Scholar
  13. 13.
    McClanahan, R.H.: The benefits of networked SCADA systems utilizing IP-enabled networks. IEEE, Los Alamitos (2002)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2010

Authors and Affiliations

  • Rafał Kozik
    • 2
  • Michał Choraś
    • 1
    • 2
  • Witold Hołubowicz
    • 1
    • 3
  1. 1.ITTI Ltd.PoznańPoland
  2. 2.Institute of TelecommunicationsUT&LS BydgoszczPoland
  3. 3.Adam Mickiewicz UniversityPoznańPoland

Personalised recommendations