There are 37 repositories under differential-privacy topic.
Fit interpretable models. Explain blackbox machine learning.
Google's differential privacy libraries.
A unified framework for privacy-preserving data analysis and machine learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Diffprivlib: The IBM Differential Privacy Library
OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.
Synthetic data generators for structured and unstructured text, featuring differentially private learning.
The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )
Simulate a federated setting and run differentially private federated learning.
Paper notes and code for differentially private machine learning
Repository for collection of research papers on privacy.
Simulation framework for accelerating research in Private Federated Learning
Differential privacy validator and runtime
Tools and service for differentially private processing of tabular and relational data
Privacy Engineering Collaboration Space
Cross-silo Federated Learning playground in Python. Discover 7 real-world federated datasets to test your new FL strategies and try to beat the leaderboard.
Awesome list for cryptographic secure computation paper. This repo includes *Lattice*, *DifferentialPrivacy*, *MPC* and also a comprehensive summary for top conferences.
Differential private machine learning
Differentially Private Optimization for PyTorch 👁🙅♀️
A codebase that makes differentially private training of transformers easy.
A curated list of resources related to privacy engineering
Synergistic fusion of privacy-enhancing technologies for enhanced privacy protection.
Code samples and documentation for SmartNoise differential privacy tools
A toolbox for differentially private data generation
Fast, memory-efficient, scalable optimization of deep learning with differential privacy
Privacy Preserving Collaborative Encrypted Network Traffic Classification (Differential Privacy, Federated Learning, Membership Inference Attack, Encrypted Traffic Classification)
Privacy-preserving generative deep neural networks support clinical data sharing
Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]