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Abstract
People are interacting with online systems all the time. In order to use the services being provided, they give consent for their data to be collected. This approach requires too much human effort and is impractical for systems like Internet-of-Things (IoT) where human-device interactions can be large. Ideally, privacy assistants can help humans make privacy decisions while working in collaboration with them. In our work, we focus on the identification and representation of privacy requirements in IoT to help privacy assistants better understand their environment. In recent years, more focus has been on the technical aspects of privacy. However, the dynamic nature of privacy also requires a representation of social aspects (e.g., social trust). In this survey paper, we review the privacy requirements represented in existing IoT ontologies. We discuss how to extend these ontologies with new requirements to better capture privacy, and we introduce case studies to demonstrate the applicability of the novel requirements.
Original language | English |
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Pages (from-to) | 163-192 |
Number of pages | 30 |
Journal | Journal of Artificial Intelligence Research |
Volume | 76 |
DOIs | |
Publication status | Published - 6 Jan 2023 |
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Dive into the research topics of 'A Survey on Understanding and Representing Privacy Requirements in IoT'. Together they form a unique fingerprint.Projects
- 1 Finished
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CONTEXT: Understanding the Role of Contexts in Managing Privacy Online Project
Kokciyan, N. (Principal Investigator) & Ogunniye, G. (Researcher)
1/06/21 → 31/05/22
Project: Research