tf-encrypted/moose
Secure distributed dataflow framework for encrypted machine learning and data processing
This framework helps data scientists, machine learning engineers, and researchers to process sensitive data and build machine learning models without directly exposing raw inputs. It takes your data and model definitions as input, then produces secure computations where data remains encrypted during processing, ensuring privacy. This is ideal for scenarios where multiple parties need to collaborate on data analysis or model training while keeping their individual contributions confidential.
No commits in the last 6 months.
Use this if you need to perform machine learning or data processing on sensitive information collaboratively across multiple parties, without revealing the underlying data to each participant.
Not ideal if your data is not sensitive, or if you need to work with highly complex machine learning models that require advanced cryptographic operations not yet supported.
Stars
70
Forks
17
Language
Rust
License
Apache-2.0
Category
Last pushed
Mar 20, 2024
Monthly downloads
5
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/tf-encrypted/moose"
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