A Design Space for Privacy Choices: Towards Meaningful Privacy Control in the Internet of Things

要旨

"Notice and choice'' is the predominant approach for data privacy protection today. There is considerable user-centered research on providing effective privacy notices but not enough guidance on designing privacy choices. Recent data privacy regulations worldwide established new requirements for privacy choices, but system practitioners struggle to implement legally compliant privacy choices that also provide users meaningful privacy control. We constructed a design space for privacy choices based on a user-centered analysis of how people exercise privacy choices in real-world systems. This work contributes a conceptual framework that considers privacy choice as a user-centered process as well as a taxonomy for practitioners to design meaningful privacy choices in their systems. We also present a use case of how we leverage the design space to finalize the design decisions for a real-world privacy choice platform, the Internet of Things (IoT) Assistant, to provide meaningful privacy control in the IoT.

著者
Yuanyuan Feng
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Yaxing Yao
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Norman Sadeh
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
DOI

10.1145/3411764.3445148

論文URL

https://doi.org/10.1145/3411764.3445148

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Privacy Design

[A] Paper Room 12, 2021-05-13 17:00:00~2021-05-13 19:00:00 / [B] Paper Room 12, 2021-05-14 01:00:00~2021-05-14 03:00:00 / [C] Paper Room 12, 2021-05-14 09:00:00~2021-05-14 11:00:00
Paper Room 12
10 件の発表
2021-05-13 17:00:00
2021-05-13 19:00:00
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