# User Perceptions of Smart Home IoT Privacy

arXiv: https://arxiv.org/abs/1802.08182 · HTML: https://mlsanity.com/paper/1802.08182/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Feb 2018.

## Built on by (most cited first, 5 of 5)

- [Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges](https://mlsanity.com/paper/2309.07438/) (2023)
- [Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way](https://mlsanity.com/paper/2110.01056/) (2021)
- [Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twitter](https://mlsanity.com/paper/2206.02156/) (2022)
- [Plural Voices, Single Agent: Towards Inclusive AI in Multi-User Domestic Spaces](https://mlsanity.com/paper/2510.19008/) (2025)
- [Contrastive Learning for Privacy Enhancements in Industrial Internet of Things](https://mlsanity.com/paper/2602.00515/) (2026)

## 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.