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Data Communication Based on MQTT in a Polymer Extrusion Process
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Lightweight Data-Security Ontology for IoT.

Pedro Gonzalez-Gil1, Juan Antonio Martinez2, Antonio F Skarmeta1

  • 1Dept. Ingeniería de la Información y las Comunicaciones, Facultad de Informática, Universidad de Murcia, 30100 Murcia, Spain.

Sensors (Basel, Switzerland)
|February 7, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces DS4IoT, a novel data-security ontology for the Internet of Things (IoT). It enhances IoT security by representing data-centric security concepts and new elements like regulations and provenance.

Keywords:
IoTcertificationdata-securityprovenanceregulationsecurity ontolgoy

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Area of Science:

  • Computer Science
  • Information Security
  • Semantic Web Technologies

Background:

  • Internet of Things (IoT) security is immature, with vulnerabilities in low-power devices and data analysis.
  • Emerging Semantic Technologies for IoT introduce new security challenges, including data markets and privacy concerns.
  • Regulations like GDPR necessitate advanced data-security approaches for personal data protection.

Purpose of the Study:

  • To present DS4IoT, a data-security ontology specifically designed for the Internet of Things.
  • To address the need for improved data security in IoT environments by adopting a data-centric perspective.
  • To incorporate novel concepts such as regulations, certifications, and provenance alongside traditional security mechanisms.

Main Methods:

  • Utilized ontological methodologies and Semantic Web best practices for ontology development.
  • Developed a bottom-up approach, focusing on data representation for security concepts.
  • Introduced implicit knowledge representation over explicit methods.

Main Results:

  • Created DS4IoT, a comprehensive data-security ontology for IoT.
  • DS4IoT covers classical security concepts (access control, authentication) and new ones (regulations, provenance).
  • The ontology serves as a common vocabulary for data annotation in IoT.

Conclusions:

  • DS4IoT offers a novel, data-centric approach to IoT security.
  • The ontology is validated through a proof of concept, mapping to the NGSI-LD data model within the IoTCrawler EU project.
  • DS4IoT advances IoT data security by integrating regulatory compliance and data provenance.