Differentially Private Spatial Decompositions

Understand

Differential privacy has recently emerged as the de facto standard for private data release.

• This makes it possible to provide strong theoretical guarantees on the privacy and utility of released data.
• While it is well-known how to release data based on counts and simple functions under this guarantee, it remains to provide general purpose techniques to release different kinds of data.
• In this paper, we focus on spatial data such as locations and more generally any data that can be indexed by a tree structure.