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Intelligent Resilience in the IoT

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SDL 2017: Model-Driven Engineering for Future Internet (SDL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10567))

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Abstract

Failing or hostile elements are normal in the public Internet of Things (IoT). Resilient IoT systems are engineered to fail safely and recover gracefully in the face of challenges presented by their environment. Approaches to ensuring resilient behaviour include intrusion detection, redundancy and self-healing. Adaptive, anomaly-based defence mechanisms are particularly well-suited to systems that are deployed in the public internet. This paper discusses the use of SDL+ (SDL with MSC and ASN.1) to generate simulation results for training anomaly-based defence mechanisms for smart systems. It outlines an approach based on the SDL+ methodology to create resilient IoT systems.

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Notes

  1. 1.

    PragmaDev Studio.

  2. 2.

    Cinderella.

  3. 3.

    IBM Rational Tau.

  4. 4.

    https://www.ll.mit.edu/ideval/data/.

  5. 5.

    https://www.quora.com/Where-can-I-get-the-latest-dataset-for-a-network-intrusion-detection-system.

  6. 6.

    http://www.sdl-forum.org/SAM_contest/Li_Probert_Williams/Railway_doc.pdf.

  7. 7.

    https://www.itu.int/en/ITU-T/asn1/Pages/introduction.aspx.

  8. 8.

    http://pragmadev.com/product/index.html.

  9. 9.

    http://www.cinderella.dk/.

References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Aberystwyth University, Aberystwyth, UK

    Edel Sherratt

Authors
  1. Edel Sherratt
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Correspondence to Edel Sherratt .

Editor information

Editors and Affiliations

  1. Ericsson Hungary, Budapest, Hungary

    Tibor Csöndes

  2. Budapest University of Technology and Economics, Budapest, Hungary

    Gábor Kovács

  3. Ericsson Hungary, Budapest, Hungary

    György Réthy

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Sherratt, E. (2017). Intelligent Resilience in the IoT. In: Csöndes, T., Kovács, G., Réthy, G. (eds) SDL 2017: Model-Driven Engineering for Future Internet. SDL 2017. Lecture Notes in Computer Science(), vol 10567. Springer, Cham. https://doi.org/10.1007/978-3-319-68015-6_4

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  • DOI: https://doi.org/10.1007/978-3-319-68015-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68014-9

  • Online ISBN: 978-3-319-68015-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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