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A Model-Driven Adaptive Approach for IoT Security

  • Conference paper
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Model-Driven Engineering and Software Development (MODELSWARD 2016)

Abstract

Internet of Things (IoT) and sensor networks are improving the cooperation between organizations, becoming more efficient and productive for the industrial systems. However, high iteration between human, machines, and heterogeneous IoT technologies increases the security threats. The IoT security is an essential requirement to fully adoption of applications, which requires correct management of information and confidentiality. The system and devices’ variability requires dynamically adaptive systems to provide services depending on the context of the environment. In this paper, we propose a model driven adaptive approach to offer security services for an ontology-based security framework. Model-Driven Engineering (MDE) approach allows creating secure capabilities more efficient with the generation of security services based on security requirements in the knowledge base (IoTSec ontology). An industrial scenario of C2NET project was analyzed to identify the transformation of a system design of security solution in a platform specific model.

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Notes

  1. 1.

    http://nvd.nist.gov/.

  2. 2.

    http://c2net-project.eu/.

  3. 3.

    http://www.w3.org/TR/rdf-sparql-query/.

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Acknowledgements

The research leading to this work has received funding from CAPES Proc. No.: BEX 0966/15-0 and European Commission’s Horizon 2020 Programme (H2020/2014-2020) under grant agreement: C2NET No.: 636909.

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Correspondence to Bruno A. Mozzaquatro .

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Mozzaquatro, B.A., Agostinho, C., Melo, R., Jardim-Goncalves, R. (2017). A Model-Driven Adaptive Approach for IoT Security. In: Hammoudi, S., Pires, L., Selic, B., Desfray, P. (eds) Model-Driven Engineering and Software Development. MODELSWARD 2016. Communications in Computer and Information Science, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-319-66302-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-66302-9_10

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  • Online ISBN: 978-3-319-66302-9

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