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This challenge is designed to help you improve your hacking skills and cybersecurity knowledge over the course of 30 days.
Adversarial attacks and defenses against federated learning.
This repository contains a 90-day cybersecurity study plan, along with resources and materials for learning various cybersecurity concepts and technologies. The plan is organized into daily tasks, covering topics such as Network+, Security+, Linux, Python, Traffic Analysis, Git, ELK, AWS, Azure, and Hacking. The repository also includes a `LEARN.md
Crab: Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Implementing ANN on NSL-KDD dataset
EDA and modeling of Anomaly Detection in IoT devices | Federated Learning | Kaggle IoT Dataset | KDD cup
Improving the Generalization of Adversarial Training with Domain Adaptation
A curated list of papers & resources linked to data poisoning, backdoor attacks and defenses against them
:books: :eyeglasses: A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
List Flower resources different videos and learning resources
:octocat: Machine Learning for Cyber Security
An opinionated list of awesome Python frameworks, libraries, software and resources.
A Survey on Vulnerability of Federated Learning: An Algorithm Perspective
Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)
Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
roadmap for a self-taught hacker
Breaching privacy in federated learning scenarios for vision and text
PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms
Set up a modern web app by running one command.
Code for Data Poisoning Attacks Against Federated Learning Systems
Defending Against Backdoor Attacks by Layer-wise Feature Analysis
The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.