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A Data-Driven Approach to Developing IoT Privacy-Setting Interfaces

https://doi.org/10.1145/3172944.3172982

Bahirat, Paritosh ; He, Yangyang ; Menon, Abhilash ; Knijnenburg, Bart ( January 2018 , 23rd International Conference on Intelligent User Interfaces)

User testing is often used to inform the development of user interfaces (UIs). But what if an interface needs to be developed for a system that does not yet exist? In that case, existing datasets can provide valuable input for UI development. We apply a data-driven approach to the development of a privacy-setting interface for Internet-of-Things (IoT) devices. Applying machine learning techniques to an existing dataset of users' sharing preferences in IoT scenarios, we develop a set of "smart" default profiles. Our resulting interface asks users to choose among these profiles, which capture their preferences with an accuracy of 82%---a 14% improvement over a naive default setting and a 12% improvement over a single smart default setting for all users.
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Scenario Context v/s Framing and Defaults in Managing Privacy in Household IoT

https://doi.org/10.1145/3180308.3180372

Bahirat, Paritosh ; Sun, Qizhang ; Knijnenburg, Bart P. ( January 2018 , Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion)

The Internet of Things provides household device users with an ability to connect and manage numerous devices over a common platform. However, the sheer number of possible privacy settings creates issues such as choice overload. This article outlines a data-driven approach to understand how users make privacy decisions in household IoT scenarios. We demonstrate that users are not just influenced by the specifics of the IoT scenario, but also by aspects immaterial to the decision, such as the default setting and its framing.
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