Intrusion detection in scada systems using one-class classification

Author

Nader, Patric ; Honeine, Paul ; Beauseroy, Pierre

Author_Institution

Inst. Charles Delaunay, Univ. de Technol. de Troyes, Troyes, France

fYear

2013

fDate

9-13 Sept. 2013

Firstpage

1

Lastpage

5

Abstract

Supervisory Control and Data Acquisition (SCADA) systems allow remote monitoring and control of critical infrastructures such as electrical power grids, gas pipelines, nuclear power plants, etc. Cyberattacks threatening these infrastructures may cause serious economic losses and may impact the health and safety of the employees and the citizens living in the area. The diversity of cyberattacks and the complexity of the studied systems make modeling cyberattacks very difficult or even impossible. This paper outlines the importance of one-class classification in detecting intrusions in SCADA systems. Two approaches are investigated, the SupportVector Data Description and the Kernel Principal Component Analysis. A case study on a gas pipeline testbed is provided with real data containing many types of cyberattacks.

Keywords

SCADA systems; critical infrastructures; pattern classification; pipelines; principal component analysis; security of data; support vector machines; SCADA systems; critical infrastructures; cyberattack modeling; cyberattacks; economic losses; electrical power grids; employee health; employee safety; gas pipeline testbed; gas pipelines; intrusion detection; kernel principal component analysis; nuclear power plants; one-class classification; remote monitoring; supervisory control and data acquisition systems; support vector data description; Computer crime; Intrusion detection; Kernel; Pipelines; SCADA systems; Support vector machines; Training; One-class classification; SCADA systems; intrusion detection; kernel methods; novelty detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European

Conference_Location

Marrakech

Type

conf

Filename

6811620