Interactive privacy management: towards enhancing privacy awareness and control in internet of things

Al Muhander, Bayan, Wiese, Jason, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646 and Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346 2023. Interactive privacy management: towards enhancing privacy awareness and control in internet of things. ACM Transactions on Internet of Things 10.1145/3600096

Preview

PDF - Accepted Post-Print Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview

Abstract

The balance between protecting user privacy while providing cost-effective devices that are functional and usable is a key challenge in the burgeoning Internet of Things (IoT). While in traditional desktop and mobile contexts, the primary user interface is a screen, in IoT devices, screens are rare or very small, invalidating many existing approaches to protecting user privacy. Privacy visualisations are a common approach for assisting users in understanding the privacy implications of web and mobile services. To gain a thorough understanding of IoT privacy, we examine existing web, mobile, and IoT visualisation approaches. Following that, we define five major privacy factors in the IoT context: (i) type, (ii) usage, (iii) storage, (iv) retention period, and (v) access. We then describe notification methods used in various contexts as reported in the literature. We aim to highlight key approaches that developers and researchers can use for creating effective IoT privacy notices that improve user privacy management (awareness and control). Using a toolkit, a use case scenario, and two examples from the literature, we demonstrate how privacy visualisation approaches can be supported in practice.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Association for Computing Machinery (ACM)
ISSN:	2691-1914
Date of First Compliant Deposit:	9 June 2023
Date of Acceptance:	9 May 2023
Last Modified:	30 Aug 2024 10:52
URI:	https://orca.cardiff.ac.uk/id/eprint/160288

Citation Data

Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item