Detect anomalies in network traffic data using Federated Machine Learning technique.
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Updated
Jul 25, 2024 - Jupyter Notebook
Detect anomalies in network traffic data using Federated Machine Learning technique.
A simple federated learning implementation on MNIST dataset using PySyft. Main goal of the project was to get used to the PySyft federated learning functionality instead of using traditional PyTorch features.
Multi-Party Computation transforms data handling by decentralizing trust among multiple participants. This ensures that no single entity demands absolute trust. An advantage for companies in safeguarding data privacy: once data leaves the user's computer, it remains obscured from any single external entity.
Securing Collaborative Medical AI by Using Differential Privacy
Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with privacy guarantees.
Material supporting the tutorial "Pursuing Privacy in Recommender Systems: The View of Users and Researchers from Regulations to Applications" held at the 15th ACM Conference on Recommender Systems in Amsterdam, Netherlands
Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning
Simple example of federated learning using torch ignite and pysyft
An implementation of Federated Learning using Pytorch and PySyft
🔥 Federated Learning Simplified with Frameworks
The implementation of the "Robust Federated Learning by Mixture of Experts" study.
Demonstration of application of Distributed Computing in Federated Learning for our Semester-8 Course on Distributed and Cloud Computing
Healthcare-Researcher-Connector Package: Federated Learning tool for bridging the gap between Healthcare providers and researchers
A collection of research and survey papers of differential privacy and federated learning
This repository will help you to understand how Federated learning can be implemented on Pima Indians Diabetic Dataset. It involves the use of OpenMined tool called Pysyft and Pytorch for implementation.
All Things Deep Learning Projects
SOON TO BE DEPRECATED - The TensorFlow bindings for PySyft
The project showcasing federated learning of model and testing on encrypted data and model
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