A unified framework for privacy-preserving data analysis and machine learning
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Updated
May 27, 2024 - Python
A unified framework for privacy-preserving data analysis and machine learning
Versatile framework for multi-party computation
Apache Teaclave (incubating) SGX SDK helps developers to write Intel SGX applications in the Rust programming language, and also known as Rust SGX SDK.
A Framework for Encrypted Machine Learning in TensorFlow
Apache Teaclave (incubating) is an open source universal secure computing platform, making computation on privacy-sensitive data safe and simple.
Enarx: Confidential Computing with WebAssembly
MPyC: Multiparty Computation in Python
A novel container runtime, aka confidential container, for cloud-native confidential computing and enclave runtime ecosystem.
Attestation and Secret Delivery Components
Cloud Stack and Solutions for Intel TDX (Trust Domain Extension)
Teaclave TrustZone SDK enables safe, functional, and ergonomic development of trustlets.
Confidential Computing Zoo provides confidential computing solutions based on Intel SGX, TDX, HEXL, etc. technologies.
EGo is an open-source SDK that enables you to develop your own confidential apps in the Go programming language.
A curated list of open-source projects that help exploit Intel SGX technology
Constellation is the first Confidential Kubernetes. Constellation shields entire Kubernetes clusters from the (cloud) infrastructure using confidential computing.
Main repository for the Veracruz privacy-preserving compute project, an adopted project of the Confidential Compute Consortium (CCC).
MarbleRun is the control plane for confidential computing. Deploy, scale, and verify your confidential microservices on vanilla Kubernetes. 100% Go, 100% cloud native, 100% confidential.
Enarx.dev website and relevant assets
Regorus - A fast, lightweight Rego (OPA policy language) interpreter written in Rust.
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