Privacy policies change management for smartphones

The ever increasing popularity of apps stems from their ability to provide highly customized services for the user. The flip side is that to provide such customized services, apps need access to very sensitive personal user information. This has led to a lot of rogue apps that e.g. pass personal information to 3^rd party Ad servers in the background. Studies have shown that current app vetting processes which are mainly restricted to install time verification mechanisms are incapable of detecting and preventing such attacks. We argue that the missing fundamental aspect here is the inability to capture and control runtime characteristics of apps, e.g. we need to know not only the list of sensors that need to be accessed by an app but also their frequency of access. This leads to the need for an expressive policy language that in addition to the list of sensors, also allows specifying when, where and how frequently can they be accessed. An expressive policy language has the disadvantage of making the task of an average user more difficult in setting and analyzing the consequences of his privacy settings. Further, privacy polices evolve over time. Over time, users are likely to change their privacy settings, as a response to a recently discovered vulnerability, or to be able to install that “much desired” app, etc. Such a policy change affects both already installed (may no longer be compliant) and previously rejected apps (may be compliant now). In this paper, we propose an integrated privacy add-on that (i) compares the apps profiles vs. user´s privacy settings, outlining the points of conflict as well as the different ways in which they can be resolved. And (ii) provides efficient change management with respect to any changes in user privacy settings.