Informing the Design of a Personalized Privacy Assistant for the Internet of Things

要旨

Internet of Things (IoT) devices create new ways through which personal data is collected and processed by service providers. Frequently, end users have little awareness of, and even less control over, these devices' data collection. IoT Personalized Privacy Assistants (PPAs) can help overcome this issue by helping users discover and, when available, control the data collection practices of nearby IoT resources. We use semi-structured interviews with 17 participants to explore user perceptions of three increasingly more autonomous potential implementations of PPAs, identifying benefits and issues associated with each implementation. We find that participants weigh the desire for control against the fear of cognitive overload. We recommend solutions that address users' differing automation preferences and reduce notification overload. We discuss open issues related to opting out from public data collections, automated consent, the phenomenon of user resignation, and designing PPAs with at-risk communities in mind.

キーワード
Internet of Things
Personalized Privacy Assistants
Inteviews
著者
Jessica Colnago
Carnegie Mellon University, Pittsburgh, PA, USA
Yuanyuan Feng
Carnegie Mellon University, Pittsburgh, PA, USA
Tharangini Palanivel
Carnegie Mellon University, Pittsburgh, PA, USA
Sarah Pearman
Carnegie Mellon University, Pittsburgh, PA, USA
Megan Ung
Carnegie Mellon University, Pittsburgh, PA, USA
Alessandro Acquisti
Carnegie Mellon University, Pittsburgh, PA, USA
Lorrie Faith Cranor
Carnegie Mellon University, Pittsburgh, PA, USA
Norman Sadeh
Carnegie Mellon University, Pittsburgh, PA, USA
DOI

10.1145/3313831.3376389

論文URL

https://doi.org/10.1145/3313831.3376389

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: IoT & wearable privacy

Paper session
313B O'AHU
5 件の発表
2020-04-27 20:00:00
2020-04-27 21:15:00
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