ldsec/drynx

Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

36
/ 100
Emerging

This library helps organizations securely analyze sensitive information spread across different locations without directly sharing the raw data. It allows you to combine data from multiple sources to perform statistical calculations or train basic machine learning models, receiving verifiable insights without compromising individual privacy. It is intended for developers building privacy-preserving data analysis systems, particularly in fields like healthcare or finance.

No commits in the last 6 months.

Use this if you need to perform statistical queries or train simple machine learning models on sensitive, distributed datasets while ensuring data privacy and verifiable results.

Not ideal if you are a non-developer seeking a ready-to-use application, or if you need to perform complex machine learning tasks beyond basic models.

data-privacy distributed-computing secure-multi-party-computation federated-learning sensitive-data-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 13 / 25

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41

Forks

6

Language

Go

License

Last pushed

Feb 25, 2023

Commits (30d)

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