Privacy-enhanced public view for social graphs

We consider the problem of releasing a limited public view of a sensitive graph which reveals at least k edges per node. We are motivated by Facebook’s public search listings, which expose user profiles to search engines along with a fixed number of each user’s friends. If this public view is produced by uniform random sampling, an adversary can accurately approximate many sensitive features of the original graph, including the degree of individual nodes. We propose several schemes to produce public views which hide degree information. We demonstrate the practicality of our schemes using real data and show that it is possible to mitigate inference of degree while still providing useful public views. Categories and Subject Descriptors K.4.1 [Computers and Society]: Public Policy Issues— Privacy; E.1 [Data Structures]: Graphs and networks; H.2.8 [Database Applications]: Data mining; K.6.5 [Management of Computing and Information Systems]: Security and Protection General Terms Se...

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: Hyoungshick Kim, Joseph Bonneau
• Keywords: CIKM 2009, Database, Facebook’s Public Search, Limited Public View, Public View