mbrg / differential-privacyLinks
Naive implementation of basic Differential-Privacy framework and algorithms
☆48Updated 2 years ago
Alternatives and similar repositories for differential-privacy
Users that are interested in differential-privacy are comparing it to the libraries listed below
Sorting:
- Code for NIPS'2017 paper☆50Updated 4 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆74Updated last year
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 4 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- Applying Laplace and exponential mechanisms to add random noise to data for differential privacy. Plotting MSE vs. epsilon.☆29Updated 4 years ago
- A Simulator for Privacy Preserving Federated Learning☆94Updated 4 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Sample LDP implementation in Python☆129Updated last year
- Accompanying source code to my Bachelor's thesis at TUHH☆11Updated 7 years ago
- ☆43Updated 3 years ago
- Differential private machine learning☆194Updated 3 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆68Updated 4 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- Multiple Frequency Estimation Under Local Differential Privacy in Python☆48Updated last year
- simple Differential Privacy in PyTorch☆48Updated 5 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 6 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆48Updated 6 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 6 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆60Updated 5 years ago
- This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)☆22Updated 5 years ago
- Differentially private learning on distributed data (NIPS 2017)☆12Updated 7 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆22Updated 4 years ago
- GFIM: An novel algorithm of frequent item mining with local differential privacy☆12Updated 5 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆33Updated 4 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆46Updated last year
- Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradi…☆31Updated 4 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆44Updated 3 years ago
- Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions☆14Updated 4 years ago