Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346, Barhamgi, Mahmoud, Bandara, Arosha K., Ajmal, Muhammad, Price, Blaine and Nuseibeh, Bashar 2019. Designing privacy-aware Internet of Things applications. Information Sciences 512 , pp. 238-257. 10.1016/j.ins.2019.09.061 |
Preview |
PDF
- Accepted Post-Print Version
Download (4MB) | Preview |
Abstract
Internet of Things (IoT) applications typically collect and analyse personal data that can be used to derive sensitive information about individuals. However, thus far, privacy concerns have not been explicitly considered in software engineering processes when designing IoT applications. The advent of behaviour driven security mechanisms, failing to address privacy concerns in the design of IoT applications can have security implications. In this paper, we explore how a Privacy-by-Design (PbD) framework, formulated as a set of guidelines, can help software engineers integrate data privacy considerations into the design of IoT applications. We studied the utility of this PbD framework by studying how software engineers use it to design IoT applications. We also explore the challenges in using the set of guidelines to influence the IoT applications design process. In addition to highlighting the benefits of having a PbD framework to make privacy features explicit during the design of IoT applications, our studies also surfaced a number of challenges associated with the approach. A key finding of our research is that the PbD framework significantly increases both novice and expert software engineers’ ability to design privacy into IoT applications.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Publisher: | Elsevier |
ISSN: | 0020-0255 |
Related URLs: | |
Date of First Compliant Deposit: | 24 April 2019 |
Date of Acceptance: | 24 September 2019 |
Last Modified: | 16 Nov 2024 23:00 |
URI: | https://orca.cardiff.ac.uk/id/eprint/121705 |
Citation Data
Cited 51 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |