A trust-based mechanism to manage user privacy in University smart buildings

Abstract

Smart buildings employ a diverse range of technologies, including sensors, to monitor the environment and create a comfortable space for users via data collection. This monitoring reveals data about users’ activities that could raise privacy concerns. In recent years, privacy has received increasing attention in smart home environments. Several studies have proposed solutions that allow smart home users to retain control over data collection and manage their privacy. However, little attention has been paid to user privacy in smart buildings that serve as places of work or study. Research on privacy in smart buildings has predominantly focused on technical aspects, with relatively limited public voice engagement in the literature. In order to effectively manage smart building environments, it is necessary to collect data. However, it is equally important to prioritise and respect the privacy principles and regulations. Users in smart buildings typically have limited or no ownership or control over captured data, along with limited awareness and insufficient disclosure from the building management which limits their ability to manage their privacy. This stands in contrast to smart home users who often possess partial ownership and control over their infrastructure. Privacy management in smart buildings poses a significant challenge, consequently, there is a need to identify a privacy design mechanism that can incorporate users’ voices into the data practices and find a balanced trade-off between the utility and privacy of smart building data. In this thesis, three studies are conducted to make significant contributions to the management of user privacy in university smart buildings. The first contribution involves analysing the impact of various building technologies on users’ privacy. These technologies are then mapped to different facets of privacy harm using the Solove taxonomy. The second contribution involves conducting semi-structured interviews to understand users’ privacy perceptions, preferences, and trade-offs, thereby identifying key requirements for privacy mechanisms in smart buildings. The third contribution involves a confirmatory study aimed at designing a privacy mechanism for smart buildings. In light of these contributions, this thesis introduces a trust-based privacy design mechanism called the Privacy Committee. The main goal of the Privacy Committee is to incorporate user voices into the decision-making process concerning data sharing and to establish comprehensive oversight of data practices within smart buildings.