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Management of secure data processing and model training as a unified sequence of operations across devices.
Distinct from Automation Workflow Management: Existing candidates focus on template managers or wallet management, not the orchestration of privacy-preserving data workflows.
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SecretFlow 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
Manages data processing and model training as a unified sequence of operations across secure devices.