The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
User Perceptions of Smart Home IoT Privacy
Open accessAbstract
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.
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Cites
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Cited by
Privacy and smart speakers: A multi-dimensional approach
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Enhancing IoT anomaly detection performance for federated learning
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New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges
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Informing the Design of Privacy-Empowering Tools for the Connected Home
Seymour, W., Kraemer, M. J., Binns, R., & Van Kleek, M. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376264 · Cited by 41
Bartle, V., Lyu, J., El Shabazz-Thompson, F., Oh, Y., Chen, A. A., Chang, Y.-J., Holstein, K., & Dell, N. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517683 · Cited by 35
Metadata
- Authors
- Zheng, S., Apthorpe, N., Chetty, M., & Feamster, N.
- Venue
- Proceedings of the ACM on Human-Computer Interaction
- Published
- 2018-11
- Volume
- 2
- Issue
- CSCW
- Pages
- 1-20
- ISSN
- 2573-0142 (ISSN-L)
- OpenAlex
- W2896396724
- Cited by
- 423
- References
- 40
- FWCI
- 68.35
- Type
- journal article
- Language
- en
- Open access
- bronze
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