This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.
☆26Oct 15, 2020Updated 5 years ago
Alternatives and similar repositories for distributedMachineLearning
Users that are interested in distributedMachineLearning are comparing it to the libraries listed below
Sorting:
- Quantifying Differential Privacy under Temporal Correlations☆12May 13, 2023Updated 2 years ago
- Code for NIPS'2017 paper☆51Jul 16, 2020Updated 5 years ago
- A Secure Multiparty Computation (MPC) protocol for computing linear regression on vertically distributed datasets.☆32Apr 16, 2019Updated 6 years ago
- Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).☆13Apr 16, 2021Updated 4 years ago
- This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"☆28Oct 3, 2022Updated 3 years ago
- Differentially Private Clustering in High-Dimensional Euclidean Spaces☆12Dec 30, 2017Updated 8 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Apr 29, 2021Updated 4 years ago
- Tool for Automating efficient Secure Two-partY computation protocols☆10Nov 10, 2016Updated 9 years ago
- Secure Interrogation of Genomic Databases (SIG-DB) using Homomorphic Encryption☆10May 16, 2018Updated 7 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆63Jun 16, 2020Updated 5 years ago
- Benchmarks for various multi-party computation frameworks☆18Oct 28, 2024Updated last year
- Malicious Two Party Computation Based on Garbled Circuits.☆12Sep 5, 2020Updated 5 years ago
- Code for computing tight guarantees for differential privacy☆23Mar 3, 2023Updated 3 years ago
- ☆184Jun 21, 2021Updated 4 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆23Aug 12, 2020Updated 5 years ago
- Prototype implementation of Prio, a system for the private computation of aggregate statistics.☆64Jan 29, 2018Updated 8 years ago
- Software for "Secure genome-wide association analysis using multiparty computation", Nature Biotechnology, 2018☆20Aug 16, 2018Updated 7 years ago
- Secure Linear Regression in the Semi-Honest Two-Party Setting.☆37Oct 1, 2019Updated 6 years ago
- Input scripts for securely evaluating quantized ImageNet models with mp-spdz☆19Oct 6, 2020Updated 5 years ago
- Code for Horizontal Federated Learning blog around Credit Scoring☆10Sep 14, 2020Updated 5 years ago
- Semi-honest Two Party Computation Based on Garbled Circuits.☆81Mar 12, 2026Updated last week
- Repository for the EDBT'23 paper "Frequency Estimation of Evolving Data Under Local Differential Privacy".☆12Aug 1, 2023Updated 2 years ago
- Crypto and networking utils used for ABY and OTExtension☆19Jul 6, 2021Updated 4 years ago
- Code for reproducing the experiments of the ICML 2019 paper "Robust Learning from Untrusted Sources"☆18Jul 5, 2019Updated 6 years ago
- ☆44Nov 23, 2021Updated 4 years ago
- Implementation of "Reading in the Dark: Classifying Encrypted Digits with Functional Encryption"☆22Jul 6, 2023Updated 2 years ago
- Code for the WWW'23 paper "Sanitizing Sentence Embeddings (and Labels) for Local Differential Privacy"☆12Feb 20, 2023Updated 3 years ago
- On Bridging Generic and Personalized Federated Learning for Image Classification☆14Feb 5, 2022Updated 4 years ago
- An Android app for the paranoids capable of remote SMS based device locking/wiping, faking the GPS and disabling the device cameras.☆11Dec 25, 2020Updated 5 years ago
- Differentially private data release for data mining [SIGKDD 2011] - convert a relational data set into a differentially-private version w…☆16Sep 11, 2015Updated 10 years ago
- 百度商业AI技术创新大赛赛道二：广告图片描述生成 Rank3方案分享☆11Oct 9, 2024Updated last year
- Python package to create a report for mobility data with differential privacy guarantees.☆15Sep 18, 2024Updated last year
- Code accompanying the paper "Disparate Impact in Differential Privacy from Gradient Misalignment".☆11Apr 4, 2023Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆137Dec 8, 2022Updated 3 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆279Dec 5, 2023Updated 2 years ago
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.☆18Mar 3, 2024Updated 2 years ago
- Pure Python Paillier Homomorphic Cryptosystem☆135Oct 17, 2018Updated 7 years ago
- ☆21May 11, 2022Updated 3 years ago
- GFIM: An novel algorithm of frequent item mining with local differential privacy☆12Feb 13, 2020Updated 6 years ago