Towards Usable Client-Centric Privacy Advisory for Mobile Collaborative Applications Based on BDDs

Considering privacy advisory for collaborative settings on mobile devices, this paper presents an innovative approach to simultaneously support dynamically reconfigurable privacy advisory and the usability of providing it. Regarded are interaction design requirements such as user-friendless and non-intrusive advisory as well as restrictions of today's mobile devices like CPU and memory consumption etc. The prototypic implementation of a client-centric privacy advisor based on binary decision diagrams shows that the proposed mechanisms integrated in an iPhone application can be effectively extended and correlated with a usable privacy-enhancing model.