Date of Award
Doctor of Philosophy (PhD)
College of Computing and Engineering
The emerging paradigm shift in technology to make everyday devices more intelligent than previously considered also known as internet of things (IoT) has further elevated the importance of privacy not only in theory but also in practice. The intrusive nature of these devices and in particular, the home automation system is also beginning to raise privacy concerns which might impact their usage either by deterring potential users from adopting the technology or discouraging existing users from the continued use of these home automation systems.
This study was an empirical and quantitative study that evaluates the impact of users’ behavior when privacy is embedded into the design of home automation systems using a web-based survey. Prior to the main study, a Delphi study and a pilot study were conducted. A 5-point Likert scale was used for the survey items which was distributed, and 330 responses were received. A pre-analysis data screening was conducted prior to the data analysis and the Partial Least Square Structural Equation Modelling (PLS-SEM) was used to analyze the collected data, while the PROCESS macro for SPSS was used to evaluate the mediation effects of the model associated with the study.
The findings from this research show the mediating effects of privacy concern on the relationship between privacy embedded design and home automation usage as well as the relationship between privacy self-efficacy and home automation usage. The study also shows that both privacy concern and home automation usage predict the two antecedents for the study. While the finding shows that the mediating effects of privacy concern on the relationship between privacy self-efficacy and home automation usage is a full mediation, the mediating effects of privacy concerns on the relationship between privacy embedded design and home automation usage shows a complementary mediating effects. The findings in this study contributes to the information systems security and privacy body of knowledge by revealing the capacity of privacy concern to predict the behavior of users of home automation usage.
Love James. 2020. Smart Privacy for IoT: Privacy Embedded Design for Home Automation Systems. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Computing and Engineering. (1116)