Privacy Protection Dashboard: A Study of Individual Cloud-Storage Users Information Privacy Protection Responses

Abstract

Cloud computing services have gained a lot of attraction in the recent years, but the shift of data from user-owned desktops and laptops to cloud storage systems has led to serious data privacy implications for the users. Even though privacy notices supplied by the cloud vendors details the data practices and options to protect their privacy, the lengthy and free-flowing textual format of the notices are often difficult to comprehend by the users. Thus we propose a simplified presentation format for privacy practices and choices termed as "Privacy-Dashboard" based on Protection Motivation Theory (PMT) and we intend to test the effectiveness of presentation format using cognitive-fit theory. Also, we indirectly model the cloud privacy concerns using Item-Response Theory (IRT) model. We contribute to the information privacy literature by addressing the literature gap to develop privacy protection artifacts in order to improve the privacy protection behaviors of individual users. The proposed "privacy dashboard" would provide an easy-to-use choice mechanisms that allow consumers to control how their data is collected and used.