Using Social Semantic Web Data for Privacy Policies

Social Web applications are steadily gaining popularity. At the same time, the open nature of such services leads to the exposure of an immense amount of personal data. Due to insufficient access control on nowadays Social Web applications problems in terms of privacy arise. This thesis focuses on the need for more flexible and fine-grained privacy restrictions. It analyses privacy problems of current Social Web applications and compares the privacy preferences such applications offer. Based on this analysis, this thesis extends the well-known principle of policy-based access control, which is a flexible and dynamic way to de ne who can get access to what content based on user preferences. The presented extension accommodates policies to the requirements of the Social Web. In particular, it describes how to exploit Social Semantic Web data for privacy reasoning. This includes the retrieval of Social and Semantic Web data from various information sources on the Web. It further includes its usage for the definition of privacy policies and its consideration during the policy evaluation. Consequently, using Social Semantic Web data for policy reasoning allows users to exactly de ne which social relationships and properties a requester has to have in order to access a particular resource. These conditions can cross the boundaries of a single Social Web application. Hence, a user can for example state that a friend on one application can access pictures stored on another application; thus bridging the walled garden of nowadays Social Web applications.