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Determination of Optimal Cluster Number in Connection to SCADA

  • Jan VávraEmail author
  • Martin Hromada
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 575)

Abstract

The recent evolution of cyber-attacks creates eminent pressure on information and communication systems. The increasing number of cyber-attacks and their sophistication have resulted in needs of the new type of cyber defense. The anomaly detection in relation to intrusion detection system (IDS) in connection with standard cyber defense technologies may be the answer to contemporary development in cyber security. Moreover, unsupervised anomaly detection based on K-means algorithm is broadly examined by a considerable number of researchers. Therefore, the algorithm is a solid selection in relation to intrusion detection system. However, one of the problems is to determine a proper number of cluster for the K-means. Nonetheless, there are methods to determine the optimal number of clusters. The aim of the article is to determine the number of clusters in relation to Supervisory Control and Data Acquisition system.

Keywords

Cyber security Clusters Anomaly detection Supervisory control Data acquisition 

Notes

Acknowledgments

This work was funded by the Internal Grant Agency (IGA/FAI/2017/003) and supported by the project ev. no. VI20152019049 “RESILIENCE 2015: Dynamic Resilience Evaluation of Interrelated Critical Infrastructure Subsystems”, supported by the Ministry of the Interior of the Czech Republic in the years 2015–2019 and also supported by the research project VI20172019054 “An analytical software module for the real-time resilience evaluation from point of the converged security”, supported by the Ministry of the Interior of the Czech Republic in the years 2017–2019. Moreover, this work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme project No. LO1303 (MSMT-7778/2014) and also by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlínCzech Republic

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