Alsufyani, Azhar A., Rana, Omer  ORCID: https://orcid.org/0000-0003-3597-2646 and Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346
2025.
Enabling collaborative anomaly exploration in smart Homes: Eliciting user requirements and security scenarios.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
9
(3)
, 68.
10.1145/3749490
|
Abstract
Smart-home technologies are becoming increasingly pervasive, automating lighting, heating, security, and other vital household functions to enhance the comfort, efficiency, and convenience of residents. However, the growing complexity and interconnectivity of these systems expose them to advanced cyber threats, putting residents' privacy and safety at risk. In this study, we investigated the design of future smart home environments to support collaborative anomaly exploration, enabling occupants and devices to jointly identify and address emerging threats. Using a mixed-methods approach---an initial questionnaire (N=40) followed by interactive focus groups (N=36)---we gathered in-depth perspectives on smart home device configurations, user workflows, and potential security vulnerabilities. Our findings include: (i) a taxonomy of realistic security threats, (ii) illustrative layouts and scenarios that highlight how anomalies emerge in everyday household routines, and (iii) concrete examples of how these anomalies can be detected collaboratively. Building on these insights, we propose a comprehensive set of design criteria to guide the development of user-centered, resilient anomaly exploration capabilities in smart homes. Our results offer recommendations for researchers, system designers, and technology practitioners seeking to balance the benefits of automation with robust user-driven security in next-generation ubiquitous home environments.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | Association for Computing Machinery (ACM) |
| ISSN: | 2474-9567 |
| Last Modified: | 10 Sep 2025 21:37 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/180923 |
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