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Diversity in Open Source Intrusion Detection Systems

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Computer Safety, Reliability, and Security (SAFECOMP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11093))

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Abstract

We present an analysis of the diversity that exists in the rules and blacklisted IP addresses of the Snort and Suricata Intrusion Detection Systems (IDSs). We analysed the evolution of the rulesets and blacklisted IP addresses of these two IDSs over a 5-month period between May and October 2017. We used three different off-the-shelf default configurations of the Snort IDS and the Emerging Threats (ET) configuration of the Suricata IDS. Analysing the differences in these systems allows us to get insights on where the diversity in the behaviour of these systems comes from and how does it evolve over time. This gives insight to Security architects on how they can combine and layer these systems in a defence-in-depth deployment. To the best of our knowledge a similar experiment has not been performed before. We will also show results on the observed diversity in behaviour of these systems, when they analysed the network data of the DMZ network of City, University of London.

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Notes

  1. 1.

    www.nsa.gov/ia/_files/support/defenseindepth.pdf.

  2. 2.

    https://github.com/shirkdog/pulledpork.

  3. 3.

    http://labs.snort.org/feeds/ip-filter.blf.

  4. 4.

    https://rules.emergingthreats.net/open/suricata/emerging.rules.tar.gz.

  5. 5.

    https://snort.org/documents/registered-vs-subscriber.

  6. 6.

    http://people.ee.duke.edu/~kst/sitar.html.

  7. 7.

    http://research.cs.ncl.ac.uk/cabernet/www.laas.research.ec.org/maftia/.

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Acknowledgment

This work was supported by the UK EPSRC project D3S and in part by the EU H2020 framework DiSIEM project.

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Correspondence to Ilir Gashi .

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Asad, H., Gashi, I. (2018). Diversity in Open Source Intrusion Detection Systems. In: Gallina, B., Skavhaug, A., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2018. Lecture Notes in Computer Science(), vol 11093. Springer, Cham. https://doi.org/10.1007/978-3-319-99130-6_18

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  • DOI: https://doi.org/10.1007/978-3-319-99130-6_18

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-99130-6

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