ABSTRACT

In this chapter, we integrate the various parts of a social media system into an automatic framework for carrying out analytics but at the same time for ensuring security. In particular, we integrate the analytics techniques in Section III with the privacy and security techniques discussed in Sections IV and V. We preserve features such as scalability, efficiency, and interoperability in developing this framework. This framework can be used to execute various policies, including access control policies, redaction policies, filtering policies, and information-sharing policies as well as inference strategies. Our framework can also be used as a testbed for evaluating different policy sets over social media graphs. Our recent work discussed in Thuraisingham et al. (2014) and Cadenhead et al. (2011) proposes new mechanisms for developing a unifying framework of data provenance expressed as Resource Description Framework (RDF) graphs. These methods can be applied for social media systems represented using semantic web technologies.