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The Role of One-Class Classification in Detecting Cyberattacks in Critical Infrastructures

  • Patric NaderEmail author
  • Paul Honeine
  • Pierre Beauseroy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8985)

Abstract

The security of critical infrastructures has gained a lot of attention in the past few years with the growth of cyberthreats and the diversity of cyberattacks. Although traditional IDS update frequently their databases of known attacks, new complex attacks are generated everyday to circumvent security systems and to make their detection nearly impossible. This paper outlines the importance of one-class classification algorithms in detecting malicious cyberattacks in critical infrastructures. The role of machine learning algorithms is complementary to IDS and firewalls, and the objective of this work is to detect intentional intrusions once they have already bypassed these security systems. Two approaches are investigated, Support Vector Data Description and Kernel Principal Component Analysis. The impact of the metric in kernels is investigated, and a heuristic for choosing the bandwidth parameter is proposed. Tests are conducted on real data with several types of cyberattacks.

Keywords

Critical infrastructures Intrusion detection One-class classification SCADA systems 

Notes

Acknowledgment

The authors would like to thank Thomas Morris and the Mississippi state university SCADA Laboratory for providing the real SCADA dataset.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institut Charles Delaunay (CNRS)Université de Technologie de TroyesTroyesFrance

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