A feature-based approach for guiding the selection of Internet of Things cybersecurity standards using text mining

Koen van der Schaaf, Bedir Tekinerdogan, Cagatay Catal*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Cybersecurity is critical in realizing Internet of Things (IoT) applications and many different standards have been introduced specifically for this purpose. However, selecting relevant standards is not trivial and requires a broad understanding of cybersecurity and knowledge about the available standards. In this study, we present a systematic approach that guides IoT system developers in selecting relevant cybersecurity standards for their IoT projects. The systematic approach has been developed in four stages. First, the common and variant features of IoT cybersecurity have been modeled using a feature model. Second, an up-to-date overview of the IoT cybersecurity standards landscape has been mapped by combining existing overviews. Third, a text mining algorithm has been implemented. Fourth, the systematic approach has been modeled using business process modeling notation. Our case study demonstrated that this approach is effective and efficient for guiding the selection of IoT cybersecurity standards.

Original languageEnglish
JournalConcurrency Computation
Volume33
Issue number21
Early online date14 Jun 2021
DOIs
Publication statusPublished - 2021

Keywords

  • cybersecurity
  • feature model
  • Internet of Things
  • natural language processing
  • standards
  • text mining

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