leriomaggio / privacy-preserving-data-science
Course Material for the Tutorial on Privacy Enhancing Technologies and PPML
☆12Updated 3 years ago
Alternatives and similar repositories for privacy-preserving-data-science:
Users that are interested in privacy-preserving-data-science are comparing it to the libraries listed below
- ☆23Updated last year
- Privacy Preserving Machine Learning (Manning Early Access Program)☆32Updated 2 years ago
- Privacy-Preserving Machine Learning (PPML) Tutorial☆37Updated 9 months ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆23Updated 5 years ago
- A toolbox for differentially private data generation☆130Updated last year
- ☆44Updated 2 years ago
- A concise primer on Differential Privacy☆28Updated 4 years ago
- A Simulator for Privacy Preserving Federated Learning☆93Updated 4 years ago
- Privacy-preserving XGBoost Inference☆48Updated last year
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS☆11Updated 2 years ago
- SAP Security research sample code and tutorials for generating differentially private synthetic datasets using generative deep learning m…☆23Updated last year
- ☆35Updated last year
- Differentially Private Optimization for PyTorch 👁🙅♀️☆184Updated 4 years ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 6 years ago
- Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning☆24Updated 2 years ago
- ☆43Updated 3 years ago
- A Federated Learning implementation to diagnose 2 acute inflammations of bladder.. This medical dataset truly needs privacy! Because we c…☆38Updated 5 years ago
- SAP Security Research sample code to reproduce the research done in our paper "Comparing local and central differential privacy using mem…☆16Updated 10 months ago
- Federated Learning is a distributed machine learning approach which enables model training on a large corpus of decentralised data. The r…☆42Updated 5 years ago
- A toolkit for tools and techniques related to the privacy and compliance of AI models.☆100Updated 8 months ago
- A library for running membership inference attacks against ML models☆142Updated 2 years ago
- ☆10Updated last year
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆66Updated 4 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆131Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆272Updated last year
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆43Updated 3 years ago
- Differential private machine learning☆190Updated 3 years ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆69Updated 6 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 6 years ago