Privacy preserving federated machine learning and block chaining for reduced cyber risks in a world of distributed healthcare

The FeatureCloud Vision The digital revolution, in particular big data and artificial intelligence (AI) offer new opportunities to transform healthcare. However, it also harbors risks to the safety of sensitive clinical data stored in critical healthcare ICT infrastructure. In particular, data exchange over the internet is perceived insurmountable, posing a roadblock hampering big data based medical innovations.

With FeatureCloud, we are involved in a pan-European transformative AI development project, which implements a software toolkit for substantially reducing cyber risks to healthcare infrastructure by employing the world-wide first privacy-by-architecture approach, which has two key characteristics: (1) no sensitive data is sent through any communication channels, and (2) data is not stored in one central point of attack.

We are in particular responsible for the creation of federated unsupervised methods, dealing with the privacy-aware federated preprocessing and clustering.

More Information can be found on the project website: https://featurecloud.eu


(Hartebrodt & Röttger, 2022) (Hartebrodt et al., 2022) (Hartebrodt & Röttger, 2022) (Hartebrodt et al., 2021) (Torkzadehmahani et al., 2020) (Matschinske et al., 2021) (Matschinske et al., 2021)
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