Secure and Accurate Federated Learning as a Service (SA-FLaaS)
Duration of the project
Source of funding
Business Finland
Total funding
636 723 €
The global federated learning market size reached USD 112.7 Million in 2021 and is expected to register a revenue CAGR of 10.5% and reach USD 305.7 Million in 2032. Federated Learning (FL) is a decentralized machine learning approach that enables model training across distributed data providers while preserving data privacy. While FL enhances data privacy and security, it faces challenges such as noise-accuracy trade-offs, system and statistical heterogeneity, communication bottlenecks, poisoning attacks, and efficiency versus privacy trade-offs.
The project builds on the PRIVASA project (2021-23), which presented award-winning FL solutions for federated tumor segmentation in brain cancer imaging. The project aims to address FL’s privacy challenges and develop a secure and efficient decentralized framework integrating differential privacy and reinforcement learning. The project´s focus includes data quality, model interpretability, and regulatory compliance in real-world healthcare settings.
The project has filed patents for two key innovations:
- Differential Privacy (DP) to enhance FL security by adding controlled noise to model updates without compromising output.
- Dynamic aggregation of model updates, selecting the most promising collaborators automatically.
These innovations align with top-tier privacy-preserving AI standards and are ready for seamless integration into FL development environments. The project´s goal is to advance to technology readiness level 7, focusing on proof-of-concept, developing test benches, and a fully operational FL platform with pioneering technologies.
The project aims to transform research into a product named “Secure and Accurate Federated Learning as a Service,” which will be the first-ever Finnish-made privacy-compliant federated learning platform.rated Learning as a Service’, the first Finnish privacy-compliant distributed machine learning platform.
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