Alternatives and similar repositories for awesome-differential-privacy:

Users that are interested in awesome-differential-privacy are comparing it to the libraries listed below

• Billy1900 / Awesome-Differential-Privacy
  Differential private machine learning
  ☆191Updated 3 years ago
• Guyanqi / Awesome-Privacy
  Repository for collection of research papers on privacy.
  ☆341Updated 8 months ago
• OpenMined / PyDP
  The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
  ☆510Updated 7 months ago
• vvv214 / LDP_Protocols
  Sample LDP implementation in Python
  ☆125Updated last year
• IBM / differential-privacy-library
  Diffprivlib: The IBM Differential Privacy Library
  ☆860Updated last week
• forestneo / sunPytools
  Useful tools for differential privacy
  ☆215Updated 2 years ago
• Samuel-Maddock / pure-LDP
  Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.
  ☆74Updated last year
• dpcomp-org / dpcomp_core
  ☆43Updated 3 years ago
• haiphanNJIT / PrivateDeepLearning
  Differential Privacy Preservation in Deep Learning under Model Attacks
  ☆133Updated 4 years ago
• yuxiangw / autodp
  autodp: A flexible and easy-to-use package for differential privacy
  ☆274Updated last year
• OpenMined / PyVertical
  Privacy Preserving Vertical Federated Learning
  ☆218Updated last year
• mortendahl / awesome-ppml
  A curated list of resources for privacy-preserving machine learning
  ☆150Updated 3 years ago
• uvm-plaid / programming-dp
  ☆312Updated 2 months ago
• ChrisWaites / pyvacy
  Differentially Private Optimization for PyTorch 👁🙅‍♀️
  ☆185Updated 4 years ago
• hharcolezi / multi-freq-ldpy
  Multiple Frequency Estimation Under Local Differential Privacy in Python
  ☆47Updated last year
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆131Updated 2 years ago
• privacytrustlab / ml_privacy_meter
  Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
  ☆636Updated 3 weeks ago
• csong27 / membership-inference
  Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
  ☆193Updated 7 years ago
• IBM / discrete-gaussian-differential-privacy
  Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010
  ☆62Updated 4 years ago
• tushar-semwal / awesome-federated-computing
  A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.
  ☆473Updated last year
• SAP-samples / machine-learning-diff-private-federated-learning
  Simulate a federated setting and run differentially private federated learning.
  ☆373Updated last month
• poga / awesome-federated-learning
  resources about federated learning and privacy in machine learning
  ☆533Updated 9 months ago
• opendp / opendp
  The core library of differential privacy algorithms powering the OpenDP Project.
  ☆351Updated this week
• mbrg / differential-privacy
  Naive implementation of basic Differential-Privacy framework and algorithms
  ☆48Updated 2 years ago
• Yangfan-Jiang / Federated-Learning-with-Differential-Privacy
  Implementation of dp-based federated learning framework using PyTorch
  ☆299Updated 2 years ago
• steven7woo / Accuracy-First-Differential-Privacy
  Code for NIPS'2017 paper
  ☆50Updated 4 years ago
• vaikkunth / PrivacyFL
  A Simulator for Privacy Preserving Federated Learning
  ☆94Updated 4 years ago
• opendp / smartnoise-sdk
  Tools and service for differentially private processing of tabular and relational data
  ☆263Updated 2 months ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆143Updated 2 years ago
• woodyx218 / Deep-Learning-with-GDP-Tensorflow
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆49Updated 3 years ago