File(s) under permanent embargo

An informed consent model for managing the privacy paradox in smart buildings

conference contribution
posted on 2020-09-01, 00:00 authored by Chehara Pathmabandu, John C Grundy, Mohan Baruwal Chhetri, Zubair BaigZubair Baig
Smart Buildings are defined as the "buildings of the future" and use the latest Internet of Things (IoT) technologies to automate building operations and services. This is to both increase operational efficiency as well as maximize occupant comfort and environmental impact. However, these "smart devices" - typically used with default settings - also enable the capture and sharing of a variety of sensitive and personal data about the occupants. Given the non-intrusive nature of most IoT devices, individuals have little awareness of what data is being collected about them and what happens to it downstream. Even if they are aware, convenience overrides any privacy concerns, and they do not take sufficient steps to control the data collection, thereby exacerbating the privacy paradox. At the same time, IoT-based building automation systems are revealing highly sensitive insights about the building occupants by synthesizing data from multiple sources and this can be exploited by the device vendors and unauthorised third parties. To address the tension between privacy and convenience in an increasingly connected world, we propose a user-centric informed consent model to foster an accurate user discretion process for privacy choice in IoT-enabled smart buildings. The proposed model aims to (a) inform and increase user awareness about how their data is being collected and used, (b) provide fine-grained visibility into privacy compliance and infringement by IoT devices, and (c) recommend corrective actions through nudges (or soft notifications). We illustrate how our proposed consent model works through a use case scenario of a voice-activated smart office.



ASEW2020: Automated Software Engineering Workshops. IEEE/ACM International Conference (35th : 2020 : Melbourne, Victoria - Online)


19 - 26


Association for Computing Machinery (ACM)



Place of publication

New York, N.Y.

Start date


End date






Publication classification

E1 Full written paper - refereed

Copyright notice

2020, Association for Computing Machinery

Title of proceedings

ASEW2020 : Proceedings of IEEE/ACM's 35th International Conference on Automated Software Engineering Workshops