TY - GEN
T1 - PARA: Privacy Management and Control in Emerging IoT Ecosystems using Augmented Reality
AU - Bermejo Fernandez, Carlos
AU - Lee, Lik Hang
AU - Nurmi, Petteri
AU - Hui, Pan
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/10/18
Y1 - 2021/10/18
N2 - The ubiquity of smart devices, combined with a lack of information about data garnered by them, make privacy a significant challenge for adopting smart devices. Ensuring users can safeguard their privacy without compromising the devices' functionality requires effective yet intuitive ways to manage personal privacy preferences. Current solutions for privacy management are severely lacking as they are ineffective in making users aware of potential privacy risks or how to mitigate them and as they offer limited support for interaction. As our first contribution, we develop a novel AR privacy management interface (PARA) that uses AR visualization to contextualize data disclosure and improve user's perceptions of privacy threats. Besides offering support for enhancing user's privacy perceptions, our interface supports privacy control on compatible devices through privacy-enhancing technologies. As our second contribution, we systematically study factors affecting privacy perceptions and privacy control for two device classes (smart camera and smart speaker) through a user study with N = 32 participants. Our results show that PARA's contextualization and visualization of privacy disclosure strongly affect the participants' privacy perceptions. For privacy control, we demonstrate that our prototype improves the participant's capability to identify risks and provides an effective and easy-to-use mechanism for controlling privacy disclosure, in contrast to existing state-of-the-art privacy management interfaces.
AB - The ubiquity of smart devices, combined with a lack of information about data garnered by them, make privacy a significant challenge for adopting smart devices. Ensuring users can safeguard their privacy without compromising the devices' functionality requires effective yet intuitive ways to manage personal privacy preferences. Current solutions for privacy management are severely lacking as they are ineffective in making users aware of potential privacy risks or how to mitigate them and as they offer limited support for interaction. As our first contribution, we develop a novel AR privacy management interface (PARA) that uses AR visualization to contextualize data disclosure and improve user's perceptions of privacy threats. Besides offering support for enhancing user's privacy perceptions, our interface supports privacy control on compatible devices through privacy-enhancing technologies. As our second contribution, we systematically study factors affecting privacy perceptions and privacy control for two device classes (smart camera and smart speaker) through a user study with N = 32 participants. Our results show that PARA's contextualization and visualization of privacy disclosure strongly affect the participants' privacy perceptions. For privacy control, we demonstrate that our prototype improves the participant's capability to identify risks and provides an effective and easy-to-use mechanism for controlling privacy disclosure, in contrast to existing state-of-the-art privacy management interfaces.
KW - AR-IoT interaction
KW - augmented reality
KW - control
KW - graphical user interfaces
KW - management
KW - mixed reality
KW - privacy
KW - smart devices
UR - http://www.scopus.com/inward/record.url?scp=85119004005&partnerID=8YFLogxK
U2 - 10.1145/3462244.3479885
DO - 10.1145/3462244.3479885
M3 - Conference article published in proceeding or book
AN - SCOPUS:85119004005
T3 - ICMI 2021 - Proceedings of the 2021 International Conference on Multimodal Interaction
SP - 478
EP - 486
BT - ICMI 2021 - Proceedings of the 2021 International Conference on Multimodal Interaction
PB - Association for Computing Machinery, Inc
T2 - 23rd ACM International Conference on Multimodal Interaction, ICMI 2021
Y2 - 18 October 2021 through 22 October 2021
ER -