An examination of privacy concerns in the Internet of Things (IoT)

: A restricted access/limited control (RALC) theory perspective

Abstract

Our global society is characterised by the revocation of fundamental human rights to privacy (i.e., Roe v. Wade) as well as the unprecedented change in the infringement of an individual’s private spaces, personal information and intimate decisions, instigated by disruptive artificial intelligence (AI) enabled technologies such as Internet of Things (IoT). Despite this, there is much dissensus in thinking about privacy in the IoT context: i) the presence of conceptual disconnectedness regarding privacy in the IoT context, ii) dysfunctional and absent application of theory in the proposed IoT privacy conceptualisations, as well as iii) the implementation of ad-hoc measurement models used to measure privacy in the IoT context. This study seeks to explore, identify and develop a contemporary and comprehensive account of privacy by extending to the IoT context the current body of knowledge on the traditional Internet context. Based on the Restricted Access, Limited Control (RALC) theory, a review of previous literature and a rigorous and comprehensive scale development process, this study presents an alternative view of privacy for the nascent environment of IoT. As a baseline, this study employs a qualitative research method with a sample of 40 experts to identify the salient privacy concerns manifestations in the IoT context. Further, with the aid of experts in the privacy domain and representatives of the relevant population (e.g. (future) users and non-users of smart technologies) the proposed privacy concerns dimensions as well as the associated measurement items are exposed to a comprehensive purification and refinement process as well as content validity evaluations. Finally, using a sample of 1,045 IoT users, three distinct privacy concerns constructs for the IoT context were found to exhibit adequate psychometric properties. This research further contributes by investigating novel theoretical linkages between under-explored constructs in the domain of privacy related IoT research.

Thesis is embargoed until 31 December 2027

Date of Award	Dec 2022
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Patrick McCole (Supervisor) & Emi Garcia-Palacios (Supervisor)