yuxiangw / autodpLinks
autodp: A flexible and easy-to-use package for differential privacy
☆278Updated 2 years ago
Alternatives and similar repositories for autodp
Users that are interested in autodp are comparing it to the libraries listed below
Sorting:
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 3 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆51Updated 7 years ago
- A library for running membership inference attacks against ML models☆152Updated 3 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- ☆80Updated 3 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆76Updated last year
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- Privacy Preserving Vertical Federated Learning☆222Updated 2 years ago
- Differential private machine learning☆199Updated 3 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆63Updated 5 years ago
- A Simulator for Privacy Preserving Federated Learning☆96Updated 5 years ago
- Breaching privacy in federated learning scenarios for vision and text☆311Updated last week
- simple Differential Privacy in PyTorch☆49Updated 5 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆152Updated 3 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆62Updated 7 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆200Updated 8 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆78Updated 2 months ago
- Algorithms to recover input data from their gradient signal through a neural network☆311Updated 2 years ago
- Code for computing tight guarantees for differential privacy☆23Updated 2 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆312Updated last year
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆697Updated 9 months ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆21Updated 5 years ago
- Code for Auditing DPSGD☆37Updated 3 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆137Updated 2 weeks ago
- Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions☆16Updated 5 years ago
- list of differential-privacy related resources☆323Updated last year
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆541Updated 2 months ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆43Updated last year