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Lookup NU author(s): Scott Harper, Dr Maryam Mehrnezhad, Dr John Mace
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© 2022 - IOS Press. All rights reserved.Smart buildings are socio-technical systems that bring together building systems, IoT technology and occupants. A multitude of embedded sensors continually collect and share building data on a large scale which is used to understand and streamline daily operations. Much of this data is highly influenced by the presence of building occupants and could be used to monitor and track their location and activities. The combination of open accessibility to smart building data and the rapid development and enforcement of data protection legislation such as the GDPR and CCPA make the privacy of smart building occupants a concern. Until now, little if any research exists on occupant privacy in work-based or commercial smart buildings. This paper addresses this gap by conducting two user studies ( N = 81 and N = 40) on privacy concerns and preferences about smart buildings. The first study explores the perception of the occupants of a state-of-the-art commercial smart building, and the latter reflects on the concerns and preferences of a more general user group who do not use this building. Our results show that the majority of the participants are not familiar with the types of data being collected, that it is subtly related to them (only 19.75% of smart building residents (occupants) and 7.5% non-residents), nor the privacy risks associated with it. After being informed more about smart buildings and the data they collect, over half of our participants said that they would be concerned with how occupancy data is used. These findings show that despite the more public environment, there are similar levels of privacy concerns for some sensors to those living in smart homes. The participants called for more transparency in the data collection process and beyond, which means that better policies and regulations should be in place for smart building data.
Author(s): Harper S, Mehrnezhad M, Mace J
Publication type: Article
Publication status: Published
Journal: Journal of Computer Security
Year: 2022
Volume: 30
Issue: 3
Pages: 465-497
Online publication date: 04/07/2022
Acceptance date: 02/04/2018
ISSN (print): 0926-227X
Publisher: IOS Press BV
URL: https://doi.org/10.3233/JCS-210035
DOI: 10.3233/JCS-210035
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