A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining. (14th June 2021)

• Record Type: Journal Article
• Authors: van der Schaaf, Koen; Tekinerdogan, Bedir; Catal, Cagatay
• Is Part Of: Concurrency and computation. Volume 33:Number 21(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-14
• Subjects: cybersecurity -- feature model -- Internet of Things -- natural language processing -- standards -- text mining; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.6385
• Languages: English
• ISSNs: 1532-0626

Abstract

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.