enList: Automatically Simplifying Privacy Policies

Online social networking sites have become extremely popular. Due to the pervasiveness of these sites, it is important to provide tools that allow users to specify detailed policies controlling access to their data. However, the policies specified using existing tools are often complex, verbose, and difficult to understand. In this paper, we study the policy simplification problem. Given a complex or verbose policy, our goal is to automatically produce an equivalent policy that is easier to understand. We propose a novel framework called enList, which automatically extracts friend "lists" (semantically meaningful subgroups of a user's friends) and then simplifies an existing policy using the lists. A laboratory-based user study confirms that the resulting policies are easier for users to comprehend, remember, and maintain than the policies produced by an existing recommendation tool.