rizwan212's Stars
Project-MONAI/tutorials
MONAI Tutorials
sarojaerabelli/py-fhe
A Python library for fully homomorphic encryption
Gharibim/federated_learning_course
Federated Learning Course Materials
FebriantiW/Homomorphic-Encryption-and-Federated-Learning-based-Privacy-Preserving-CNN-Training-
Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learn- ing techniques, has been started to use for the improvement of the privacy and security of medical data. In the federated learning, the training data is distributed across multiple machines, and the learning process is performed in a collaborative manner. There are several privacy attacks on deep learning (DL) models to get the sensitive information by attackers. Therefore, the DL model itself should be protected from the adversarial attack, especially for applications using medical data. One of the solutions for this prob- lem is homomorphic encryption-based model protection from the adversary collaborator. This paper proposes a privacy-preserving federated learning algorithm for medical data using homomor- phic encryption. The proposed algorithm uses a secure multi-party computation protocol to protect the deep learning model from the adversaries. In this study, the proposed algorithm using a real-world medical dataset is evaluated in terms of the model performance.
VectorInstitute/PETs-Bootcamp
A collection of demos and utilities prepared ahead of the Vector Institute Privacy Enhancing Techniques (PETs) Bootcamp.
dilbwagsingh/HAR-using-Federated-Learning
santteegt/fl-algorithms
Repository containing notebooks that implement different Federated Learning algorithms using PyTorch
ameliajimenez/curriculum-federated-learning
Memory-aware curriculum federated learning for breast cancer classification. Computer Methods and Programs in Biomedicine.
OpenMined/syft-heart-disease-tutorial
destiny301/PMFL
[BigData2022] PMFL: Partial Meta-Federated Learnig
nliulab/FL-Benchmark
Valentyn1997/seal-regression
Linear Regression on Homomorphic Encrypted Data, based on PySEAL package
JoshuaChou2018/PPPML-HMI
KaranJoseph/Retinal_OCT
Federated Learning with Differential Privacy + MLflow & Optuna
MaxvanHaastrecht/Federated-Learning-Analytics
A repository with Python code, in the form of understandable Jupyter Notebooks, to facilitate federated learning with the educational analytics datasets OULAD, EdNet, and KDD Cup 2015.
Arjun-08/Federated-learning-over-IOMT
This project implements federated learning using a ResNet-34 model to classify chest X-ray images into various medical conditions. By distributing the training process across multiple clients holding local datasets, the approach ensures data privacy and leverages the power of decentralized learning.
Arjun-08/Image-classification-model
This repository hosts code for a deep learning project focused on classifying chest X-ray images into normal and abnormal categories, with a specific emphasis on detecting COVID-19 and pneumonia cases. Leveraging convolutional neural networks (CNNs) and transfer learning methodologies, the project aims to achieve precise classification outcomes.
BernardoPulido/HE-Comparison
Towards Understanding Efficient Privacy-Preserving Homomorphic Comparison
khaustova/fully-homomorphic-encryption-in-machine-learning
Исследование использования полностью гомоморфного шифрования для защиты данных в машинном обучении
mohres/Private-FL
Differentially Private Federated Learning (DPFL) for medical image classification using PyTorch
srirangamuc/fed-learn
A Collection of Markdowns and Notebooks used during my research on Federated Learning
devilhyt/ecg-federated-learning-public
edgaromons/Federated-and-Deep-Learning-Based-Intrusion-Detection-System-for-Internet-of-Things
In this Notebook, we show how to build a Federated and Deep Learning Based Intrusion Detection System for Internet of Things (IoT). Application is also included.
elebrasy/TWML_pytorch_project
Trustworthy Machine Leaning course project.
HaoPham23/PPML-with-CKKS
jiahuigeng/FederatedLearningBooK
lngquoctrung/MNIST_FNN_Differential_Privacy
mollyolzinski/Federated-Learning
Neurohackademy 2024 Federated Learning repository
robinkoestler/A-survey-on-modern-fully-homomorphic-encryption
SimuEnv/Federated-Analytics