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All in One! User Perceptions on Centralized IoT Privacy Settings

Marky, Karola ; Zimmermann, Verena ; Stöver, Alina ; Hoffmann, Philipp ; Kunze, Kai ; Mühlhäuser, Max (2020):
All in One! User Perceptions on Centralized IoT Privacy Settings.
In: CHI'20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems,
ACM, 38th CHI Conference on Human Factors in Computing Systems, virtual Conference, 25.-30.04.2020, ISBN 978-1-4503-6819-3,
DOI: 10.1145/3334480.3383016,
[Conference or Workshop Item]

Abstract

IoT devices deliver their functionality by accessing data. Users decide which data they are willing to share via privacy settings interfaces that are typically on the device, or in the app controlling it. Thus, users have to interact with each device or app which is time-consuming and settings might be overlooked. In this paper, we provide a stepping stone into a multi-device interface for adjusting privacy settings. We present three levels of information detail: 1) sensor name 2), sensor name and information about captured data and 3) detailed information on each collected data type including consequences. Through a pre-study with 15 participants, we found that users prefer the access to detailed information because this offers the best decision support. They also wish for a clear status communication, a possibility for rule-based settings, and delegation options.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Marky, Karola ; Zimmermann, Verena ; Stöver, Alina ; Hoffmann, Philipp ; Kunze, Kai ; Mühlhäuser, Max
Title: All in One! User Perceptions on Centralized IoT Privacy Settings
Language: English
Abstract:

IoT devices deliver their functionality by accessing data. Users decide which data they are willing to share via privacy settings interfaces that are typically on the device, or in the app controlling it. Thus, users have to interact with each device or app which is time-consuming and settings might be overlooked. In this paper, we provide a stepping stone into a multi-device interface for adjusting privacy settings. We present three levels of information detail: 1) sensor name 2), sensor name and information about captured data and 3) detailed information on each collected data type including consequences. Through a pre-study with 15 participants, we found that users prefer the access to detailed information because this offers the best decision support. They also wish for a clear status communication, a possibility for rule-based settings, and delegation options.

Book Title: CHI'20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
Publisher: ACM
ISBN: 978-1-4503-6819-3
Uncontrolled Keywords: privacy decision support, smart home, internet of things
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Telecooperation
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 2050 Privacy and Trust for Mobile Users
03 Department of Human Sciences
03 Department of Human Sciences > Institute for Psychology
03 Department of Human Sciences > Institute for Psychology > Engineering psychology research group!
Event Title: 38th CHI Conference on Human Factors in Computing Systems
Event Location: virtual Conference
Event Dates: 25.-30.04.2020
Date Deposited: 26 Jun 2020 07:55
DOI: 10.1145/3334480.3383016
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