Aegis: A semantic implementation of privacy as contextual integrity in social ecosystems

Combining and incorporating rich semantics of user social data, which is currently fragmented and managed by proprietary applications, has the potential to more accurately represent a user´s social ecosystems. However, social ecosystems raise even more serious privacy concerns than today´s social networks. This paper proposes to model privacy as contextual integrity by using semantic web tools and focuses on defining default privacy policies, as they have the highest impact. Through a real implementation and performance evaluation we show that such a framework is practical.