research
∙
09/15/2023
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms
Synthetic data generation methods, and in particular, private synthetic ...
share
research
∙
08/30/2023
Publishing Wikipedia usage data with strong privacy guarantees
For almost 20 years, the Wikimedia Foundation has been publishing statis...
research
∙
12/20/2022
PreFair: Privately Generating Justifiably Fair Synthetic Data
When a database is protected by Differential Privacy (DP), its usability...
research
∙
12/19/2022
Multi-Analyst Differential Privacy for Online Query Answering
Most differentially private mechanisms are designed for the use of a sin...
research
∙
12/08/2022
Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy
In this short paper, we outline the design of Tumult Analytics, a Python...
research
∙
09/07/2022
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census
The purpose of this paper is to guide interpretation of the semantic pri...
research
∙
09/02/2022
DPXPlain: Privately Explaining Aggregate Query Answers
Differential privacy (DP) is the state-of-the-art and rigorous notion of...
research
∙
04/19/2022
The 2020 Census Disclosure Avoidance System TopDown Algorithm
The Census TopDown Algorithm (TDA) is a disclosure avoidance system usin...
research
∙
03/09/2022
IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy
In this paper, we consider secure outsourced growing databases that supp...
research
∙
12/16/2021
Benchmarking Differentially Private Synthetic Data Generation Algorithms
This work presents a systematic benchmark of differentially private synt...
research
∙
11/08/2021
Equity and Privacy: More Than Just a Tradeoff
While the entire field of privacy preserving data analytics is focused o...
research
∙
07/22/2021
Differentially Private Algorithms for 2020 Census Detailed DHC Race & Ethnicity
This article describes a proposed differentially private (DP) algorithms...
research
∙
06/23/2021
HDMM: Optimizing error of high-dimensional statistical queries under differential privacy
In this work we describe the High-Dimensional Matrix Mechanism (HDMM), a...
research
∙
06/09/2021
Prior-Aware Distribution Estimation for Differential Privacy
Joint distribution estimation of a dataset under differential privacy is...
research
∙
03/29/2021
DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy
In this paper, we have introduced a new type of leakage associated with ...
research
∙
03/26/2021
Synthesizing Linked Data Under Cardinality and Integrity Constraints
The generation of synthetic data is useful in multiple aspects, from tes...
research
∙
11/02/2020
Budget Sharing for Multi-Analyst Differential Privacy
Large organizations that collect data about populations (like the US Cen...
research
∙
04/19/2020
DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications
Differential privacy (DP) has arisen as the state-of-the-art metric for ...
research
∙
04/09/2020
Computing Local Sensitivities of Counting Queries with Joins
Local sensitivity of a query Q given a database instance D, i.e. how muc...
research
∙
08/27/2019
Answering Summation Queries for Numerical Attributes under Differential Privacy
In this work we explore the problem of answering a set of sum queries un...
research
∙
07/03/2019
Capacity Bounded Differential Privacy
Differential privacy, a notion of algorithmic stability, is a gold stand...
research
∙
05/29/2019
Fair Decision Making using Privacy-Protected Data
Data collected about individuals is regularly used to make decisions tha...
research
∙
02/20/2019
Outis: Crypto-Assisted Differential Privacy on Untrusted Servers
Differential privacy has steadily become the de-facto standard for achie...
research
∙
10/03/2018
Shrinkwrap: Differentially-Private Query Processing in Private Data Federations
A private data federation is a set of autonomous databases that share a ...
research
∙
08/10/2018
Ektelo: A Framework for Defining Differentially-Private Computations
The adoption of differential privacy is growing but the complexity of de...
research
∙
08/10/2018
Optimizing error of high-dimensional statistical queries under differential privacy
Differentially private algorithms for answering sets of predicate counti...
research
∙
04/02/2018
Differentially Private Hierarchical Count-of-Counts Histograms
We consider the problem of privately releasing a class of queries that w...
research
∙
04/02/2018
Differentially Private Hierarchical Group Size Estimation
Consider the problem of estimating, for every integer j, the number of h...
research
∙
12/29/2017
Private Exploration Primitives for Data Cleaning
Data cleaning is the process of detecting and repairing inaccurate or co...
research
∙
12/16/2017
