Aljeraisy, Atheer, Rana, Omer  ORCID: https://orcid.org/0000-0003-3597-2646 and Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346
2023.
Canella: Privacy-aware end-to-end integrated IoT development ecosystem.
Presented at: IEEE International Conference on Pervasive Computing and Communications,
Atlanta, USA,
13-17 March 2023.
Proceedings of International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).
IEEE,
pp. 279-281.
10.1109/PerComWorkshops56833.2023.10150254
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Abstract
Applications for the Internet of Things (IoT) can derive sensitive information about people, so developers must protect users’ privacy in compliance with privacy and data protection laws. However, developers face difficulties in addressing privacy issues as many applications exploit personal data in a problematic manner. We present Canella, an integrated IoT development ecosystem that is augmented with novel privacy-preserving components for developing privacy-aware IoT applications. Canella helps software developers meet privacy requirements during the development phase and during rapid prototyping, and it provides real-time feedback on potential privacy concerns. Canella aims at assisting developers to (i) better understand their code’s behavior, (ii) better overcome privacy issues and comply with privacy and data protection laws, (iii) reduce time to incorporate privacy into an IoT application, and (iv) reduce the cognitive load of integrating privacy into an IoT application. Thus, Canella can result in a significant improvement in building privacy-aware IoT applications.
| Item Type: | Conference or Workshop Item - published (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Publisher: | IEEE |
| ISBN: | 9781665453820 |
| ISSN: | 2836-5348 |
| Date of Acceptance: | 5 January 2023 |
| Last Modified: | 25 Aug 2026 22:06 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/156343 |
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