Skip to content
#

dataprivacy

Here are 19 public repositories matching this topic...

This repository contains a project showcasing Federated Learning using the EMNIST dataset. Federated Learning is a privacy-preserving machine learning approach that allows a model to be trained across multiple decentralized devices or servers holding local data samples, without exchanging them.

  • Updated Sep 24, 2023
  • Jupyter Notebook

This code has been developed to address the vulnerability associated with an exposed port, which could potentially serve as an entry point for malicious attacks. For illustrative purposes, consider the scenario where port 6***1 is left open and responds to SYN scans.

  • Updated Aug 10, 2023
  • C++

Improve this page

Add a description, image, and links to the dataprivacy topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the dataprivacy topic, visit your repo's landing page and select "manage topics."

Learn more