A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).

Writing AI Conference Papers: A Handbook for Beginners

A Framework for Encrypted Machine Learning in TensorFlow

A FRamework for Efficient Secure COmputation

Secure distributed dataflow framework for encrypted machine learning and data processing

A curated list of resources for using LLMs to develop more competitive grant applications.

Companion webpage to the book "Mathematics For Machine Learning"

A unified framework for privacy-preserving data analysis and machine learning

Repository for collection of research papers on multi-party learning.

A web GUI client of Project V which supports V2Ray, Xray, SS, SSR, Trojan and Pingtunnel 🚀

Paper Notes in MPC with Applications to PPML

A curated list of multi party computation resources and links.

Secure Multi-Party Computation (MPC) with Go. This project implements secure two-party computation with Garbled circuit protocol.

Oblivious transfer (OT) communications protocol message/response functionality implementations based on Curve25519 and the Ristretto group.

Federated learning on graph and tabular data related papers, frameworks, and datasets.

freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.

📚 Freely available programming books

📚 免费的计算机编程类中文书籍，欢迎投稿

A incomplete survey for Split Learning (comprehensive enough) and Federated Learning (only most representative works)

A curated list of resources for privacy-preserving machine learning

This is the demo codes for our corresponding paper

Define and run multi-container applications with Docker