Flotta让多方在高安全环境下协作训练模型，适用于生物医学等敏感数据场景。
Flotta: a Secure and Flexible Spark-inspired Federated Learning Framework
- 基于Spark思想设计，支持多机构安全协同训练
- 可在联盟内部机器上运行，无需外部依赖
- 适合生物医学等需严防数据泄露的研究团队
我们提出Flotta，一个联邦学习框架，旨在安全地训练分布在多方联盟中的敏感数据上的机器学习模型，适用于对安全性要求极高的研究领域，如生物医学。Flotta是一个受Apache Spark启发的Python包，兼具灵活性与安全性，支持仅使用联盟内部机器开展研究。本文介绍了框架的核心组件，并通过实际应用场景展示其能力，突出其安全性、灵活性和易用性。
原文摘要 · Abstract (English)
We present Flotta, a Federated Learning framework designed to train machine learning models on sensitive data distributed across a multi-party consortium conducting research in contexts requiring high levels of security, such as the biomedical field. Flotta is a Python package, inspired in several aspects by Apache Spark, which provides both flexibility and security and allows conducting research using solely machines internal to the consortium. In this paper, we describe the main components of the framework together with a practical use case to illustrate the framework's capabilities and highlight its security, flexibility and user-friendliness.
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