Automating the Generation of Privacy Policies for Context-Sharing Applications

Abstract

Enabling the automated recognition and sharing of a user's context is a primary motivation for many pervasive computing applications. In the past, a significant amount of research has been focusing on the aspect of effective and efficient recognition. Yet, when context is shared with others, the resulting disclosure of personal information can have undesirable privacy implications. A common solution to this problem is the manual creation of an application-specific privacy policy that defines which information may be shared with whom. However, as the number of applications increases, such a manual approach becomes increasingly cumbersome and over time, it is likely to lead to incomplete or even inconsistent policies. In this paper, we discuss how a privacy policy can be derived automatically by analyzing the user's sharing behaviour when using online collaboration tools. Our approach retrieves shared content and the associated sharing settings, detects context types and automatically derives a privacy policy that reflects the user's past sharing behaviour. To validate our approach, we have implemented it as an extensible software library for the Android platform and we have developed plug-ins for two popular collaboration tools, namely Google Calendar and Facebook.