Synthesizing and modeling privacy-by-design knowledge For IoT applications

Alkhariji, Lamya 2023. Synthesizing and modeling privacy-by-design knowledge For IoT applications. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

As Internet of Things (IoT) technologies become increasingly integrated into our daily lives, concerns about privacy have risen significantly. This research aims to address these privacy issues by providing software engineers with a method to understand and implement Privacy by Design (PbD) practices during the system design phase. We synthesized and collected PbD schemes and employed semantic web technologies to model the knowledge encompassing PbD schemes, their intersections with Privacy Patterns, IoT system requirements, and the applicable Privacy Patterns for these IoT systems. This thesis introduces the PARROT ontology, which consolidates this wealth of knowledge. To develop the PARROT ontology, we associated real-world IoT use cases with well-established Privacy Patterns that software developers should apply. We gathered Competency Questions (CQs) about these IoT use cases through workshops with researchers and software developers, resulting in 81 CQs for modeling. We validated and evaluated the PARROT ontology, addressing common pitfalls with tools such as Protégé & HermiT Reasoner and Ontology Pitfall Scanner (OOPS!),alongside external expert input. Through a user-based study, we demonstrated the practical use of the PARROT ontology and found that it can answer up to 58% of software engineers’questions, making it a valuable resource for enhancing privacy practices in IoT system development. Finally, we demonstrated the seamless integration of the PARROT ontology into a chatbot interface.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Computer Science & Informatics
Uncontrolled Keywords:	Computer Science
Date of First Compliant Deposit:	24 October 2024
Date of Acceptance:	20 October 2024
Last Modified:	25 Oct 2024 09:41
URI:	https://orca.cardiff.ac.uk/id/eprint/173317

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