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Awesome GitHub RepositoriesPrivacy Computing Frameworks
Integrated platforms for executing secure multi-party computation and privacy-preserving machine learning.
Distinct from Privacy-Preserving Compute Engines: Shortlist candidates focus on specific engines or ML techniques, not the overarching framework identity.
Explore 1 awesome GitHub repository matching security & cryptography · Privacy Computing Frameworks. Refine with filters or upvote what's useful.
Awesome Privacy Computing Frameworks GitHub Repositories
Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
- secretflow/secretflow
secretflow/secretflow
2,629Ver en GitHubSecretFlow is a privacy computing framework and platform designed for secure multi-party computation, federated learning, and privacy-preserving data analysis across independent nodes. It provides a management system to coordinate secure workloads and cryptographic tasks across a distributed cluster. The project enables joint data analysis and machine learning on partitioned datasets using cryptographic protocols. It allows for the training of models and the execution of analytical queries across multiple parties without exposing raw source information to any single participant. The framewor
Provides a comprehensive framework for secure multi-party computation and privacy-preserving machine learning across distributed nodes.
Pythonconfidential-computingdata-analysisdifferential-privacy
