Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.

Multiple Frequency Estimation Under Local Differential Privacy in Python

Implementation of local differential privacy mechanisms in Python language.

Source code for LDPTrace: Locally Differentially Private Trajectory Synthesis. VLDB 2023.

PyTorch implementation of a number of mechanisms in local differential privacy

Apple Differential Privacy Implementation

Repository for the EDBT'23 paper "Frequency Estimation of Evolving Data Under Local Differential Privacy".

Repository for the DBSec 2023 paper "(Local) Differential Privacy has NO Disparate Impact on Fairness"

Repository for the VLDB'23 paper "On the Risks of Collecting Multidimensional Data Under Local Differential Privacy"

LDP-Toolbox: Exploring Utility and Attackability Tradeoffs in Local Differential Privacy

TrasgoDP implements a set of mechanisms for Local Differential Privacy (LDP). It is particularly well-suited for generating synthetic versions of a dataset using mechanisms that also ensure differential privacy.

A single-file CLI that generates privacy-preserving synthetic CSVs via local differential privacy (Laplace & randomized response).

Privacy-Preserving Genomic Statistical Analysis Under Local Differential Privacy

Implements and evaluates TrieHH and SFP heavy-hitter algorithms under local differential privacy, including full data preprocessing, simulation, and F1-score analysis on Wikipedia Clickstream. Designed for reproducible experiments and privacy–utility benchmarking.

Comp430 Project

Repository for the experiments in the article "Lightweight Protocols for Distributed Private Quantile Estimation"