Alternatives and similar repositories for privacybuckets

Users that are interested in privacybuckets are comparing it to the libraries listed below

• bargavj / distributedMachineLearning
  This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.
  ☆26Updated 4 years ago
• IBM / discrete-gaussian-differential-privacy
  Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010
  ☆61Updated 4 years ago
• sunblaze-ucb / dpml-benchmark
  This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.
  ☆64Updated 6 years ago
• dpcomp-org / dpcomp_core
  ☆43Updated 3 years ago
• schoppmp / linreg-mpc
  A Secure Multiparty Computation (MPC) protocol for computing linear regression on vertically distributed datasets.
  ☆32Updated 6 years ago
• pps-lab / rofl-project-code
  ☆32Updated 2 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆134Updated 2 years ago
• LaRiffle / ariann
  Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing
  ☆51Updated 3 years ago
• csiro-mlai / deep-mpc
  ☆36Updated 6 months ago
• LaRiffle / collateral-learning
  Collateral Learning - Functional Encryption and Adversarial Training on partially encrypted networks
  ☆76Updated 9 months ago
• ftramer / Handcrafted-DP
  ☆80Updated 2 years ago
• cleverhans-lab / capc-iclr
  CaPC is a method that enables collaborating parties to improve their own local heterogeneous machine learning models in a setting where b…
  ☆26Updated 3 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆34Updated 4 years ago
• mortendahl / awesome-ppml
  A curated list of resources for privacy-preserving machine learning
  ☆150Updated 3 years ago
• OpenMined / sycret
  Function Secret Sharing library for Python and Rust with hardware acceleration (PETS '22)
  ☆57Updated last year
• BorjaBalle / analytic-gaussian-mechanism
  Analytic calibration for differential privacy with Gaussian perturbations
  ☆47Updated 6 years ago
• snwagh / securenn-public
  Implementation of protocols in SecureNN.
  ☆129Updated 2 years ago
• ppml-news / ppml-news.github.io
  News in Privacy-Preserving Machine Learning
  ☆12Updated 5 years ago
• OpenMined / SyMPC
  A SMPC companion library for Syft
  ☆103Updated last week
• tf-encrypted / tf-seal
  Bridge between TensorFlow and the Microsoft SEAL homomorphic encryption library
  ☆95Updated 5 years ago
• SSGAalto / minionn
  Privacy -preserving Neural Networks
  ☆78Updated 6 years ago
• ektelo / ektelo
  ☆38Updated 2 years ago
• marcoszh / BatchCrypt
  ☆87Updated 4 years ago
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆73Updated last year
• steven7woo / Accuracy-First-Differential-Privacy
  Code for NIPS'2017 paper
  ☆50Updated 4 years ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 5 years ago
• inspire-lab / CryptoDL
  Privacy-preserving Deep Learning based on homomorphic encryption (HE)
  ☆34Updated 3 years ago
• loretanr / dp-gbdt
  GBDT learning + differential privacy. Standalone C++ implementation of "DPBoost" (Li et al.). There are further hardened & SGX versions o…
  ☆8Updated 2 years ago
• corentingiraud / federated-learning-secure-aggregation
  A simple Python implementation of a secure aggregation protocole for federated learning.
  ☆35Updated 2 years ago
• mc2-project / delphi
  A Cryptographic Inference Service for Neural Networks
  ☆130Updated 9 months ago