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A Data-Driven Approach to Designing for Privacy in Household IoT

A Data-Driven Approach to Designing for Privacy in Household IoT In this article, we extend and improve upon a previously developed data-driven approach to design privacy-setting interfaces for users of household IoT devices. The essence of this approach is to gather users’ feedback on household IoT scenarios before developing the interface, which allows us to create a navigational structure that preemptively maximizes users’ efficiency in expressing their privacy preferences, and develop a series of ‘privacy profiles’ that allow users to express a complex set of privacy preferences with the single click of a button. We expand upon the existing approach by proposing a more sophisticated translation of statistical results into interface design, and by extensively discussing and analyzing the tradeoff between user-model parsimony and accuracy in developing privacy profiles and default settings. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Interactive Intelligent Systems (TiiS) Association for Computing Machinery

A Data-Driven Approach to Designing for Privacy in Household IoT

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2019 ACM
ISSN
2160-6455
eISSN
2160-6463
DOI
10.1145/3241378
Publisher site
See Article on Publisher Site

Abstract

In this article, we extend and improve upon a previously developed data-driven approach to design privacy-setting interfaces for users of household IoT devices. The essence of this approach is to gather users’ feedback on household IoT scenarios before developing the interface, which allows us to create a navigational structure that preemptively maximizes users’ efficiency in expressing their privacy preferences, and develop a series of ‘privacy profiles’ that allow users to express a complex set of privacy preferences with the single click of a button. We expand upon the existing approach by proposing a more sophisticated translation of statistical results into interface design, and by extensively discussing and analyzing the tradeoff between user-model parsimony and accuracy in developing privacy profiles and default settings.

Journal

ACM Transactions on Interactive Intelligent Systems (TiiS) – Association for Computing Machinery

Published: Sep 26, 2019

Keywords: Designing for IoT

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