Private frequency estimation via projective geometry
In this work, we propose a new algorithm ProjectiveGeometryResponse (PGR) for locally
differentially private (LDP) frequency estimation. For universe size of k and with n users, our …
differentially private (LDP) frequency estimation. For universe size of k and with n users, our …
[PDF][PDF] FELIP: A local Differentially Private approach to frequency estimation on multidimensional datasets.
JS da Costa Filho, JC Machado - EDBT, 2023 - openproceedings.org
Local Differential Privacy (LDP) allows answering queries on users data while maintaining
their privacy. Queries are often issued on multidimensional datasets with categorical and …
their privacy. Queries are often issued on multidimensional datasets with categorical and …
Locally differentially private frequency estimation with consistency
Local Differential Privacy (LDP) protects user privacy from the data collector. LDP protocols
have been increasingly deployed in the industry. A basic building block is frequency oracle …
have been increasingly deployed in the industry. A basic building block is frequency oracle …
Differentially private fractional frequency moments estimation with polylogarithmic space
We prove that $\mathbb {F} _p $ sketch, a well-celebrated streaming algorithm for frequency
moments estimation, is differentially private as is when $ p\in (0, 1] $. $\mathbb {F} _p …
moments estimation, is differentially private as is when $ p\in (0, 1] $. $\mathbb {F} _p …
[HTML][HTML] Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates
This paper investigates the problem of collecting multidimensional data throughout time (ie,
longitudinal studies) for the fundamental task of frequency estimation under Local …
longitudinal studies) for the fundamental task of frequency estimation under Local …
Incorporating prior knowledge in local differentially private data collection for frequency estimation
Local differential privacy (LDP) is a prevalent measure of privacy protection as it provides
rigorous privacy guarantees and has been widely studied for statistical analysis, especially …
rigorous privacy guarantees and has been widely studied for statistical analysis, especially …
Communication complexity in locally private distribution estimation and heavy hitters
We consider the problems of distribution estimation, and heavy hitter (frequency) estimation
under privacy, and communication constraints. While the constraints have been studied …
under privacy, and communication constraints. While the constraints have been studied …
Calibrate: Frequency estimation and heavy hitter identification with local differential privacy via incorporating prior knowledge
Estimating frequencies of certain items among a population is a basic step in data analytics,
which enables more advanced data analytics (eg, heavy hitter identification, frequent pattern …
which enables more advanced data analytics (eg, heavy hitter identification, frequent pattern …
Frequency estimation under local differential privacy [experiments, analysis and benchmarks]
Private collection of statistics from a large distributed population is an important problem,
and has led to large scale deployments from several leading technology companies. The …
and has led to large scale deployments from several leading technology companies. The …
Sarve: synthetic data and local differential privacy for private frequency estimation
The collection of user attributes by service providers is a double-edged sword. They are
instrumental in driving statistical analysis to train more accurate predictive models like …
instrumental in driving statistical analysis to train more accurate predictive models like …