On the Risks of Collecting Multidimensional Data Under Local Differential Privacy

09/04/2022
by   Héber H. Arcolezi, et al.
1

The private collection of multiple statistics from a population is a fundamental statistical problem. One possible approach to realize this is to rely on the local model of differential privacy (LDP). Numerous LDP protocols have been developed for the task of frequency estimation of single and multiple attributes. These studies mainly focused on improving the utility of the algorithms to ensure the server performs the estimations accurately. In this paper, we investigate privacy threats (re-identification and attribute inference attacks) against LDP protocols for multidimensional data following two state-of-the-art solutions for frequency estimation of multiple attributes. To broaden the scope of our study, we have also experimentally assessed five widely used LDP protocols, namely, generalized randomized response, optimal local hashing, subset selection, RAPPOR and optimal unary encoding. Finally, we also proposed a countermeasure that improves both utility and robustness against the identified threats. Our contributions can help practitioners aiming to collect users' statistics privately to decide which LDP mechanism best fits their needs.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/08/2021

Improving the Utility of Locally Differentially Private Protocols for Longitudinal and Multidimensional Frequency Estimates

This paper investigates the problem of collecting multidimensional data ...
research
09/15/2021

Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy

With local differential privacy (LDP), users can privatize their data an...
research
06/28/2019

Collecting and Analyzing Multidimensional Data with Local Differential Privacy

Local differential privacy (LDP) is a recently proposed privacy standard...
research
10/01/2022

Frequency Estimation of Evolving Data Under Local Differential Privacy

Collecting and analyzing evolving longitudinal data has become a common ...
research
03/30/2021

Frequency Estimation under Local Differential Privacy [Experiments, Analysis and Benchmarks]

Private collection of statistics from a large distributed population is ...
research
05/15/2019

Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy

Local Differential Privacy (LDP) is popularly used in practice for priva...
research
11/22/2021

Poisoning Attacks to Local Differential Privacy Protocols for Key-Value Data

Local Differential Privacy (LDP) protocols enable an untrusted server to...

Please sign up or login with your details

Forgot password? Click here to reset