Website for Privacy Engineering Program at CMU
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Updated
May 26, 2024 - HTML
Website for Privacy Engineering Program at CMU
StatsPro is a open-source, easily deployable, and privacy friendly alternative to Google Analytics.
FedAnil+ is a novel lightweight, and secure Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil+ written in Python.
FedAnil is a secure blockchain-enabled Federated Deep Learning Model to address non-IID data and privacy concerns. This repo hosts a simulation for FedAnil written in Python.
My Privacy DNS #Matrix lists for blacklisting
Distributed, collaborative, offline-first time tracking app ⏱
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A unified framework for privacy-preserving data analysis and machine learning
SPU (Secure Processing Unit) aims to be a provable, measurable secure computation device, which provides computation ability while keeping your private data protected.
Privacy-Preserving Machine Learning (PPML) Tutorial
Privacy-Preserving Computing Platform 由密码学专家团队打造的开源隐私计算平台,支持多方安全计算、联邦学习、隐私求交、匿踪查询等。
Easy PSI is a web platform focused on Private Set Intersection(PSI), which is based on Kuscia and SecretFlow PSI Library.
A STARK-based ZKVM which aims to Programmable Scalability, Programmable Privacy
Go implementation of Waku v2 protocol
Golang implementation of the PlatON protocol
A client side tier list maker, without any ads
Kuscia(Kubernetes-based Secure Collaborative InfrA) is a K8s-based privacy-preserving computing task orchestration framework.
Decentralized & federated privacy-preserving ML training, using p2p networking, in JS
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