mbrg / differential-privacyLinks
Naive implementation of basic Differential-Privacy framework and algorithms
☆48Updated 3 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☆51Updated 5 years ago
- ☆45Updated 4 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆78Updated 3 weeks ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 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
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 5 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆51Updated 7 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆276Updated 2 years ago
- Differential private machine learning☆196Updated 3 years ago
- Privacy Preserving Vertical Federated Learning☆220Updated 2 years ago
- Sample LDP implementation in Python☆128Updated 2 years ago
- list of differential-privacy related resources☆317Updated 10 months ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆21Updated 5 years ago
- ☆90Updated 5 years ago
- Useful tools for differential privacy☆219Updated 3 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 7 years ago
- Applying Laplace and exponential mechanisms to add random noise to data for differential privacy. Plotting MSE vs. epsilon.☆30Updated 5 years ago
- Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing☆51Updated 4 years ago
- A Simulator for Privacy Preserving Federated Learning☆96Updated 4 years ago
- Privacy -preserving Neural Networks☆79Updated 6 years ago
- MPC Secure Multiparty Computation. A three-party secret-sharing-based vertical federated learning setting. The data are vertically parti…☆24Updated 6 years ago
- Privacy-preserving Deep Learning based on homomorphic encryption (HE)☆35Updated 4 years ago
- simple Differential Privacy in PyTorch☆49Updated 5 years ago
- Privacy-Preserving Deep Learning via Additively Homomorphic Encryption☆72Updated 4 years ago
- Repository for collection of research papers on privacy.☆342Updated last year
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆92Updated 6 years ago
- SecMML (Queqiao): Secure MPC (multi-party computation) Machine Learning Framework.☆113Updated 2 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆67Updated 4 years ago