Effects of contextual properties on users' privacy preferences in mobile computing environments

Abstract

Malicious mobile applications exploit users' private information that is not directly related to the provision of services that the users want to access. In current mobile computing environments, it is hard for users to detect whether an application commits privacy infringement once they have given permissions to the application. Context-based access control is one of the major approaches for dealing with the privacy infringement problem because users usually make decisions on allowing applications to access their private information based on their contextual situations. However, there has been no study analyzing which contextual information is especially crucial for users to make appropriate privacy decisions. In this paper, we conducted an intensive survey and analysis to identify what types of contextual information are essential for understanding users' privacy preferences in mobile computing environments. We present how to effectively collect both users' privacy preferences and contextual information, and analyze the characteristics of users' privacy preferences. In the course of analysis, to improve the accuracy of deducing the contextual properties and privacyrules, we developed an approach of effectively detecting and handling the inconsistent privacy preferences referred to as the privacy paradox and turbulence phenomena. As the result, we found that five contextual properties affect users' privac ypreferences most.