Private Query Release via the Johnson-Lindenstrauss Transform
Private Query Release via the Johnson-Lindenstrauss Transform
We introduce a new method for releasing answers to statistical queries with differential privacy, based on the Johnson-Lindenstrauss lemma. The key idea is to randomly project the query answers to a lower dimensional space so that the distance between any two vectors of feasible query answers is preserved up to …