19 results found Sort:

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Created 2019-10-19
131 commits to master branch, last one 6 months ago
341
1.7k
apache-2.0
46
Training PyTorch models with differential privacy
Created 2019-12-07
733 commits to main branch, last one 2 days ago
A Privacy-Preserving Framework Based on TensorFlow
Created 2020-04-08
463 commits to master branch, last one 2 years ago
17
188
apache-2.0
32
Privacy Testing for Deep Learning
Created 2020-05-22
190 commits to master branch, last one about a year ago
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Created 2020-06-12
166 commits to master branch, last one 2 years ago
Implementation of protocols in SecureNN.
Created 2019-02-20
9 commits to master branch, last one 2 years ago
Fast, memory-efficient, scalable optimization of deep learning with differential privacy
Created 2022-11-20
183 commits to main branch, last one 25 days ago
Piranha: A GPU Platform for Secure Computation
Created 2022-05-20
32 commits to main branch, last one about a year ago
Implementation of protocols in Falcon
Created 2020-05-19
27 commits to master branch, last one 2 years ago
17
79
mit
6
Advanced Privacy-Preserving Federated Learning framework
Created 2021-10-07
1,167 commits to main branch, last one 26 days ago
13
47
apache-2.0
2
Privacy Preserving Convolutional Neural Network using Homomorphic Encryption for secure inference
Created 2020-09-22
9 commits to master branch, last one 3 years ago
15
46
gpl-2.0
7
This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.
Created 2020-12-14
39 commits to main branch, last one 2 years ago
12
43
cc0-1.0
2
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)
Created 2021-08-19
537 commits to master branch, last one about a year ago
[ICML 2022 / ICLR 2024] Source code for our papers "Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks" and "Be Careful What You Smooth For".
Created 2022-01-31
55 commits to master branch, last one 3 months ago
Privacy-Preserving Machine Learning (PPML) Tutorial
Created 2022-04-12
118 commits to main branch, last one 5 months ago
A library for statistically estimating the privacy of ML pipelines from membership inference attacks
Created 2022-08-03
29 commits to main branch, last one 8 months ago