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Effect of Network Architecture Changes on OCSVM Based Intrusion Detection System

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Abstract

Intrusion Detection Systems are becoming an important defense mechanism for (supervisory control and data acquisition (SCADA) systems. SCADA systems are likely to become more dynamic leading to a need for research into how changes to the network architecture that is monitored, affect the performance of defense mechanisms. This article investigates how changes in the network architecture of the SCADA system affect the performance of an IDS that is based on the One class Support Vector Machine (OCSVM). Also the article proposes an adaptive mechanism that can cope with such changes and can work in real time situations.

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References

  1. Kim, H.: Security and vulnerability of scada systems over ip-based wireless sensor networks. Int. J. Distrib. Sensor Netw. 2012, 1–10 (2012)

    Google Scholar 

  2. Yang, Y., McLaughlin, K., Sezer, S., Littler, T., Im, E.G., Pranggono, B., Wang, H.: Multiattribute scada-specific intrusion detection system for power networks. IEEE Trans. Power Deliv. 29(3), 1092–1102 (2014)

    Article  Google Scholar 

  3. Igure, V.M., Laughter, S.A., Williams, R.D.: Security issues in scada networks. Comput. Secur. 25(7), 498–506 (2006)

    Article  Google Scholar 

  4. Nicholson, A., Webber, S., Dyer, S., Patel, T., Janicke, H.: Scada security in the light of cyber-warfare. Comput. Secur. 31(4), 418–436 (2012)

    Article  Google Scholar 

  5. Maglaras, L.A., Jiang, J., Cruz, T.: Integrated ocsvm mechanism for intrusion detection in scada systems. Electron. Lett. 50(25), 1935–1936 (2014)

    Article  Google Scholar 

  6. Maglaras, L.A., Jiang, J., Cruz, T.J.: Combining ensemble methods and social network metrics for improving accuracy of OCSVM on intrusion detection in SCADA systems. J. Inform. Secur. Appl. 30, 15–26 (2016)

    Google Scholar 

  7. Pandit, T., Dudy, A.: An artificial neural network based approach for dos attacks detection in manet (2014)

    Google Scholar 

  8. Wang, Y., Wong, J., Miner, A.: Anomaly intrusion detection using one class svm. In: Information Assurance Workshop, 2004, Proceedings from the Fifth Annual IEEE SMC, pp. 358–364. IEEE (2004)

    Google Scholar 

  9. Kim, D.S., Nguyen, H.-N., Park, J.S.: Genetic algorithm to improve svm based network intrusion detection system. In: 19th International Conference on Advanced Information Networking and Applications, AINA 2005, vol. 2, pp. 155–158. IEEE (2005)

    Google Scholar 

  10. Maglaras, L.A., Jiang, J.: Ocsvm model combined with k-means recursive clustering for intrusion detection in scada systems. In: 2014 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine), pp. 133–134. IEEE (2014)

    Google Scholar 

  11. Cruz, T., Proença, J., Simões, P., Aubigny, M., Ouedraogo, M., Graziano, A., Yasakhetu, L.: Improving cyber-security awareness on industrial control systems: the cockpitci approach. In: 13th European Conference on Cyber Warfare and Security ECCWS-2014 The University of Piraeus Piraeus, Greece, p. 59 (2014)

    Google Scholar 

  12. Cheung, S., Dutertre, B., Fong, M., Lindqvist, U., Skinner, K., Valdes, A.: Using model-based intrusion detection for scada networks. In: Proceedings of the SCADA Security Scientific Symposium, vol. 46, pp. 1–12. Citeseer (2007)

    Google Scholar 

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Correspondence to Leandros Maglaras .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Stewart, B., Rosa, L., Maglaras, L., Cruz, T.J., Simões, P., Janicke, H. (2017). Effect of Network Architecture Changes on OCSVM Based Intrusion Detection System. In: Maglaras, L., Janicke, H., Jones, K. (eds) Industrial Networks and Intelligent Systems. INISCOM 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 188. Springer, Cham. https://doi.org/10.1007/978-3-319-52569-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-52569-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52568-6

  • Online ISBN: 978-3-319-52569-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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