Content-Based Privacy Management on the Social Web

Protection of privacy is a major concern for users of social web applications, including social networks. Although most online social networks now offer fine-grained controls of information sharing, these are rarely used, both because their use imposes additional burden on the user and because they are too complex for an average user to handle. To mitigate the problem, we propose an intelligent privacy manager that automates the assignment of sharing permissions, taking into account the content of the published information and user´s high-level sharing policies. At the core of our contribution is a novel privacy policy language which explicitly accounts for social web concepts and which balances the expressive power with representation complexity. The manager employs named entity recognition algorithms to annotate sensitive parts of published information and an answer set programming system to evaluate user´s privacy policies and determine the list of safe recipients. We implemented a prototype of the manager on the Face book platform. On a small test scenario, the manager reached the F-measure value of 0.831 in correctly recommending safe recipients.