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Intrusion Detection for Sequence-Based Attacks with Reduced Traffic Models

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10740))

Abstract

Securing control networks (e.g. for power and gas distribution) requires dedicated approaches. Sequence-aware intrusion detection models the network traffic under normal operation to identify malicious behavior. Unfortunately, such models are often large and difficult to handle. This paper proposes a method that generates smaller traffic models and discusses the accuracy of those reduced models in the context of a real control infrastructure employing the IEC 60870-5-104 protocol.

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Notes

  1. 1.

    See also: https://github.com/jjchromik/intravis/blob/master/example/over.pdf.

  2. 2.

    See also: https://github.com/jjchromik/intravis/blob/master/example/all.pdf.

  3. 3.

    The code used to modify the traces is available on github https://github.com/penc4ke/manipulateTraces.git.

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Correspondence to Justyna Chromik .

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Ferling, B., Chromik, J., Caselli, M., Remke, A. (2018). Intrusion Detection for Sequence-Based Attacks with Reduced Traffic Models. In: German, R., Hielscher, KS., Krieger, U. (eds) Measurement, Modelling and Evaluation of Computing Systems. MMB 2018. Lecture Notes in Computer Science(), vol 10740. Springer, Cham. https://doi.org/10.1007/978-3-319-74947-1_4

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  • DOI: https://doi.org/10.1007/978-3-319-74947-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74946-4

  • Online ISBN: 978-3-319-74947-1

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