User Perceptions of Smart Home IoT Privacy
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Abstract (arXiv)
Smart home Internet of Things (IoT) devices are rapidly increasing in popularity, with more households including Internet-connected devices that continuously monitor user activities. In this study, we conduct eleven semi-structured interviews with smart home owners, investigating their reasons for purchasing IoT devices, perceptions of smart home privacy risks, and actions taken to protect their privacy from those external to the home who create, manage, track, or regulate IoT devices and/or their data. We note several recurring themes. First, users' desires for convenience and connectedness dictate their privacy-related behaviors for dealing with external entities, such as device manufacturers, Internet Service Providers, governments, and advertisers. Second, user opinions about external entities collecting smart home data depend on perceived benefit from these entities. Third, users trust IoT device manufacturers to protect their privacy but do not verify that these protections are in place. Fourth, users are unaware of privacy risks from inference algorithms operating on data from non-audio/visual devices. These findings motivate several recommendations for device designers, researchers, and industry standards to better match device privacy features to the expectations and preferences of smart home owners.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2018.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 1.
5 papers.
- 2023Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challengescited by 14
- 2021Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Waycited by 1
- 2022Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twittercited by 1
- 2025Plural Voices, Single Agent: Towards Inclusive AI in Multi-User Domestic Spacescited by 0
- 2026Contrastive Learning for Privacy Enhancements in Industrial Internet of Thingscited by 0
- 2026Contrastive Learning for Privacy Enhancements in Industrial Internet of Things31 Jan 2026
- 2025Plural Voices, Single Agent: Towards Inclusive AI in Multi-User Domestic Spaces21 Oct 2025
- 2023Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges14 Sep 2023
- 2022Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twitter5 Jun 2022
- 2021Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way3 Oct 2021