privacy-preserving-machine-learning

There are 19 repositories under privacy-preserving-machine-learning topic.

EthicalML / awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
awesome awesome-list data-mining deep-learning explainability interpretability large-scale-machine-learning large-scale-ml machine-learning machine-learning-operations ml-operations ml-ops mlops privacy-preserving privacy-preserving-machine-learning privacy-preserving-ml production-machine-learning production-ml responsible-ai
17325
jphall663 / awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
ai-safety awesome awesome-list data-science explainable-ml fairness interpretability interpretable-ai interpretable-machine-learning interpretable-ml machine-learning machine-learning-interpretability privacy-enhancing-technologies privacy-preserving-machine-learning python r reliable-ai secure-ml transparency xai
3588
innovation-cat / Awesome-Federated-Machine-Learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
federated-learning machine-learning deep-learning privacy-preserving-machine-learning computer-vision distributed-computing edge-computing security differential-privacy
1715
pytorch / opacus
Training PyTorch models with differential privacy
differential-privacy privacy-preserving-machine-learning deep-learning machine-learning neural-network pytorch
Language:Jupyter Notebook 1679
securefederatedai / openfl
An open framework for Federated Learning.
federated-learning secure-computation openfl distributed-computing deep-learning collaborative-learning privacy-preserving-machine-learning machine-learning fedprox fedavg federated-analytics python federated-learning-framework federated-deep-learning pytorch-federated-learning tensorflow-federated-learning keras-federated-learning distributed-learning fedcurv fedopt
Language:Jupyter Notebook 709
LatticeX-Foundation / Rosetta
A Privacy-Preserving Framework Based on TensorFlow
privacy-preserving-machine-learning secure-multiparty-computation homomorphic-encryption zero-knowledge-proofs federated-learning secure-computation
Language:C++ 560
PrivacyRaven
trailofbits / PrivacyRaven
Privacy Testing for Deep Learning
machine-learning deep-learning python privacy privacy-preserving-machine-learning privacy-enhancing-technologies membership-inference model-extraction model-inversion
Language:Python 184
microsoft / robustdg
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
artificial-intelligence causality domain-generalization machine-learning privacy-preserving-machine-learning
Language:Python 171
snwagh / securenn-public
Implementation of protocols in SecureNN.
multi-party-computation private-deep-learning privacy-preserving-machine-learning
Language:C++ 121
snwagh / falcon-public
Implementation of protocols in Falcon
multi-party-computation secure-computation privacy-enhancing-technologies privacy-preserving-machine-learning
Language:C++ 90
ucbrise / piranha
Piranha: A GPU Platform for Secure Computation
gpu-acceleration multi-party-computation privacy-preserving-machine-learning
Language:C++ 88
awslabs / fast-differential-privacy
Fast, memory-efficient, scalable optimization of deep learning with differential privacy
deep-learning differential-privacy neural-network privacy-preserving-machine-learning
Language:Python 86
APPFL / APPFL
Advanced Privacy-Preserving Federated Learning framework
federated-learning-framework privacy-preserving-machine-learning
Language:Python 71
DiscreetAI / decentralized-ml
Full stack service enabling decentralized machine learning on private data
machine-learning decentralized-machine-learning federated-learning python javascript privacy privacy-enhancing-technologies privacy-preserving-machine-learning deep-learning deep-neural-networks swift tensorflow pytorch compression-algorithm
Language:Jupyter Notebook 61
yamanalab / PP-CNN
Privacy Preserving Convolutional Neural Network using Homomorphic Encryption for secure inference
privacy-preserving-machine-learning private-deep-learning ppml
Language:C++ 45
ayushm-agrawal / Federated-Learning-Implementations
This repository contains all the implementation of different papers on Federated Learning
federated-learning pytorch pytorch-implementation privacy-preserving-machine-learning fedavg fedprox
Language:Jupyter Notebook 43
FIGLAB / Vid2Doppler
This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.
human-computer-interaction human-activity-recognition human-pose-tracking doppler privacy-preserving-machine-learning
Language:Python 43
sisaman / GAP
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)
deep-learning pytorch differential-privacy graph-neural-networks pytorch-geometric graph-deep-learning privacy-preserving-machine-learning
Language:Jupyter Notebook 42
leriomaggio / ppml-tutorial
Privacy-Preserving Machine Learning (PPML) Tutorial
data-science deep-learning machine-learning privacy-enhancing-technologies privacy-preserving privacy-preserving-machine-learning trustworthy-machine-learning tutorial
Language:Jupyter Notebook 36
shreya-28 / Secure-ML
Secure Linear Regression in the Semi-Honest Two-Party Setting.
secure-ml secure-multi-party-computation linear-regression privacy-preserving-machine-learning
Language:C++ 36
dilawarm / federated
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data
federated-learning homomorphic-encryption differential-privacy tensorflow privacy-preserving-machine-learning security
Language:Python 34
LukasStruppek / Plug-and-Play-Attacks
[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".
face-recognition privacy-preserving-machine-learning privacy-attacks model-inversion machine-learning stylegan2 model-inversion-attacks
Language:Jupyter Notebook 34
responsible-ai-toolbox-privacy
microsoft / responsible-ai-toolbox-privacy
A library for statistically estimating the privacy of ML pipelines from membership inference attacks
machine-learning privacy-preserving-machine-learning
Language:Python 31
hharcolezi / ldp-protocols-mobility-cdrs
Implementation of local differential privacy mechanisms in Python language.
differential-privacy local-differential-privacy privacy-preserving-machine-learning privacy ldp data-privacy differential-privacy-deep-learning machine-learning
Language:Jupyter Notebook 27
JiangChSo / PFLM
Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradients. To achieve robustness to users dropping out, existing practical privacy-preserving federated learning schemes are based on (t, N)-threshold secret sharing. Such schemes rely on a strong assumption to guarantee security: the threshold t must be greater than half of the number of users. The assumption is so rigorous that in some scenarios the schemes may not be appropriate. Motivated by the issue, we first introduce membership proof for federated learning, which leverages cryptographic accumulators to generate membership proofs by accumulating users IDs. The proofs are issued in a public blockchain for users to verify. With membership proof, we propose a privacy-preserving federated learning scheme called PFLM. PFLM releases the assumption of threshold while maintaining the security guarantees. Additionally, we design a result verification algorithm based on a variant of ElGamal encryption to verify the correctness of aggregated results from the cloud server. The verification algorithm is integrated into PFLM as a part. Security analysis in a random oracle model shows that PFLM guarantees privacy against active adversaries. The implementation of PFLM and experiments demonstrate the performance of PFLM in terms of computation and communication.
privacy-preserving privacy-preserving-machine-learning federated-learning membership blockchain
Language:Jupyter Notebook 26
chamathpali / FedSim
Similarity Guided Model Aggregation for Federated Learning
federated-learning deep-learning machine-learning privacy-preserving-machine-learning
Language:Python 24
mmalekzadeh / privacy-preserving-bandits
Privacy-Preserving Bandits (MLSys'20)
bandit-algorithms differential-privacy machine-learning online-machine-learning reinforcement-learning contextual-bandits privacy-preserving-machine-learning privacy-preserving-bandits criteo-dataset federated-learning recommender-system recommendation bandit-learning bandit-algorithm differentially-private
Language:Jupyter Notebook 22
AlanPeng0897 / Defend_MI
Bilateral Dependency Optimization: Defending Against Model-inversion Attacks
model-inversion-attacks privacy-preserving-machine-learning
Language:Python 21
athenarc / smpc-analytics
📊 Privacy Preserving Medical Data Analytics using Secure Multi Party Computation. An End-To-End Use Case. A. Giannopoulos, D. Mouris M.Sc. thesis at the University of Athens, Greece.
smpc-analytics mpc privacy-preserving privacy-preserving-machine-learning privacy-preserving-analytics privacy histograms decision-trees
Language:Python 19
amartya18x / tapas
Tricks for Accelerating (encrypted) Prediction As a Service
privacy-preserving-machine-learning binary-neural-networks homomorphic-encryption
Language:HTML 18
Lucieno / gforce-public
A crypto-assisted framework for protecting the privacy of models and queries in inference.
secure-computation privacy-preserving-machine-learning cryptography python pytorch
Language:Python 18
inaccel / heflow
Open source platform for the privacy-preserving machine learning lifecycle
homomorphic-encryption privacy-preserving-machine-learning
Language:Python 16
mikeroyal / Differential-Privacy-Guide
Differential Privacy Guide
privacy-enhancing-technologies machine-learning privacy decentralization decentralized decentralized-applications deep-learning privacy-preserving privacy-preserving-machine-learning privacy-protection awesome awesome-resources differential-privacy
Language:Python 14
TTitcombe / NoPeekNN
PyTorch implementation of NoPeekNN
nopeeknn pytorch splitnn privacy-preserving-machine-learning privacy-preserving split-neural-network
Language:Jupyter Notebook 14
barlettacarmen / CrCNN
Crypto-Convolutional Neural Network library written on top of SEAL 2.3.1
homomorphic-encryption convolutional-neural-networks seal cryptography privacy-preserving-machine-learning
Language:C++ 13
eric-ai-lab / FedVLN
[ECCV 2022] Official pytorch implementation of the paper "FedVLN: Privacy-preserving Federated Vision-and-Language Navigation"
federated-learning privacy-preserving-machine-learning vision-and-language-navigation
Language:C++ 13

privacy-preserving-machine-learning

EthicalML / awesome-production-machine-learning

jphall663 / awesome-machine-learning-interpretability

innovation-cat / Awesome-Federated-Machine-Learning

pytorch / opacus

securefederatedai / openfl

LatticeX-Foundation / Rosetta

trailofbits / PrivacyRaven

microsoft / robustdg

snwagh / securenn-public

snwagh / falcon-public

ucbrise / piranha

awslabs / fast-differential-privacy

APPFL / APPFL

DiscreetAI / decentralized-ml

yamanalab / PP-CNN

ayushm-agrawal / Federated-Learning-Implementations

FIGLAB / Vid2Doppler

sisaman / GAP

leriomaggio / ppml-tutorial

shreya-28 / Secure-ML

dilawarm / federated

LukasStruppek / Plug-and-Play-Attacks

microsoft / responsible-ai-toolbox-privacy

hharcolezi / ldp-protocols-mobility-cdrs

JiangChSo / PFLM

chamathpali / FedSim

mmalekzadeh / privacy-preserving-bandits

AlanPeng0897 / Defend_MI

athenarc / smpc-analytics

amartya18x / tapas

Lucieno / gforce-public

inaccel / heflow

mikeroyal / Differential-Privacy-Guide

TTitcombe / NoPeekNN

barlettacarmen / CrCNN

eric-ai-lab / FedVLN