Log In Sign Up

Differentially private partition selection

by   Damien Desfontaines, et al.

Many data analysis operations can be expressed as a GROUP BY query on an unbounded set of partitions, followed by a per-partition aggregation. To make such a query differentially private, adding noise to each aggregation is not enough: we also need to make sure that the set of partitions released is also differentially private. This problem is not new, and it was recently formally introduced as differentially private set union. In this work, we continue this area of study, and focus on the common setting where each user is associated with a single partition. In this setting, we propose a simple, optimal differentially private mechanism that maximizes the number of released partitions. We discuss implementation considerations, as well as the possible extension of this approach to the setting where each user contributes to a fixed, small number of partitions.


page 1

page 2

page 3

page 4


Colored Noise Mechanism for Differentially Private Clustering

The goal of this paper is to propose and analyze a differentially privat...

FriendlyCore: Practical Differentially Private Aggregation

Differentially private algorithms for common metric aggregation tasks, s...

Permute-and-Flip: A new mechanism for differentially private selection

We consider the problem of differentially private selection. Given a fin...

Differentially Private Set Union

We study the basic operation of set union in the global model of differe...

Differentially Private n-gram Extraction

We revisit the problem of n-gram extraction in the differential privacy ...

Majority Vote for Distributed Differentially Private Sign Selection

Privacy-preserving data analysis has become prevailing in recent years. ...

Private Multi-Group Aggregation

We study the differentially private multi group aggregation (PMGA) probl...