Differential private machine learning
☆201Feb 10, 2022Updated 4 years ago
Alternatives and similar repositories for Awesome-Differential-Privacy
Users that are interested in Awesome-Differential-Privacy are comparing it to the libraries listed below
Sorting:
- Repository for collection of research papers on privacy.☆345Jul 19, 2024Updated last year
- Implementation of dp-based federated learning framework using PyTorch☆315Jan 3, 2026Updated 2 months ago
- list of differential-privacy related resources☆325Jan 10, 2025Updated last year
- Differentially private federated learning: A systematic review (ACM Survey); Adap dp-fl: Differentially private federated learning with a…☆381Sep 2, 2025Updated 6 months ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆46Nov 28, 2022Updated 3 years ago
- 本项目实现自《差分隐私下满足一致性的轨迹流量发布方法》,作者蔡剑平☆12Sep 2, 2019Updated 6 years ago
- Diffprivlib: The IBM Differential Privacy Library☆906Sep 17, 2025Updated 5 months ago
- This repo implements several algorithms for learning with differential privacy.☆110Dec 15, 2022Updated 3 years ago
- Quantifying Differential Privacy under Temporal Correlations☆12May 13, 2023Updated 2 years ago
- A curated list of awesome privacy preserving machine learning resources☆14May 17, 2020Updated 5 years ago
- Code for NIPS'2017 paper☆51Jul 16, 2020Updated 5 years ago
- A foundational platform that primarily shares federated learning, differential privacy content☆27Mar 19, 2025Updated 11 months ago
- Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shak…☆421Oct 26, 2024Updated last year
- code for 'Differential Location Privacy for Sparse Mobile Crowdsensing' at ICDM'16☆47Jan 19, 2017Updated 9 years ago
- ConTPL: Controlling Temporal Privacy Leakage in Streaming Data Release with Differential Privacy☆10Sep 7, 2018Updated 7 years ago
- The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation☆170Dec 11, 2022Updated 3 years ago
- Applying Laplace and exponential mechanisms to add random noise to data for differential privacy. Plotting MSE vs. epsilon.☆31Dec 20, 2025Updated 2 months ago
- Training PyTorch models with differential privacy☆1,908Feb 26, 2026Updated last week
- autodp: A flexible and easy-to-use package for differential privacy☆278Dec 5, 2023Updated 2 years ago
- Simulate a federated setting and run differentially private federated learning.☆387Mar 7, 2025Updated last year
- Code for AAAI 2021 Paper "Membership Privacy for Machine Learning Models Through Knowledge Transfer"☆11Apr 5, 2021Updated 4 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Mar 1, 2018Updated 8 years ago
- 建立基于差分隐私的贝叶斯网络,使得结构化数据同时兼备隐私性与效用性☆29Jan 31, 2021Updated 5 years ago
- ☆27Dec 15, 2022Updated 3 years ago
- ☆333Dec 25, 2025Updated 2 months ago
- Sample LDP implementation in Python☆128Jul 26, 2023Updated 2 years ago
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆543Nov 7, 2025Updated 4 months ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Apr 25, 2022Updated 3 years ago
- Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"☆13Nov 19, 2021Updated 4 years ago
- Differential Privacy Protection against MembershipInference Attack on Machine Learning for Genomic Data☆19Aug 4, 2020Updated 5 years ago
- The core library of differential privacy algorithms powering the OpenDP Project.☆409Updated this week
- Analytic calibration for differential privacy with Gaussian perturbations☆51Oct 7, 2018Updated 7 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆85Nov 22, 2021Updated 4 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆46Feb 12, 2019Updated 7 years ago
- Library for training machine learning models with privacy for training data☆1,999Updated this week
- Privacy-Preserving Data Analysis using Pandas☆23Oct 16, 2021Updated 4 years ago
- The core code for our paper "Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning".☆21Dec 25, 2023Updated 2 years ago
- Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)☆76Feb 9, 2025Updated last year
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆63Jun 16, 2020Updated 5 years ago