LPS22 Programme

C1.01.1 Trusted Machine Learning - security, privacy and confidentiality in EO data ecosystems GO BACK

Chairs: Anna Burzykowska (ESA - European Space Agency), Dr. Arne Raulf (DLR Institute for AI Safety and Security)

08:30 08:45	Applying Technologies from the Gaia-X Infrastructure Model for Trustworthy EO Data Ecosystems. Lessons Learnt from Data Exchange Use Cases in the Automotive Network Catena-X Presenter: Emma Smith (Fetch.ai), Dr. Arne Raulf (DLR Institute for AI Safety and Security)
08:45 09:00	BLENDED - Executing Machine Learning Applications in a Secured and Decentralised Platform Presenter: Bernard Valentin (Space Applications Services SA/NV)
09:00 09:15	A review of Privacy-Preserving techniques for Statistical and Earth Observation data including an approach for privately mapping socioeconomic population indicators with Sentinel-2 and Census Data Presenter: David Smith (DEIMOS Space UK Ltd.)
09:15 09:30	Merging and Analyzing Fishing data for Science and Management Whilst Remaining Secure and Confidential Presenter: Gonçalo Sousa Mendes (Elecnor Deimos)
09:30 09:45	Federated Learning for Vessel Detection with AIS as Training data Presenter: Gonçalo Sousa Mendes (Elecnor Deimos)
09:45 10:00	MPC4SaferLearn – a novel framework for Secure, Robust, and Privacy Preserving Collaborative Machine Learning on Highly Sensitive Data Presenter: Dr. Katarzyna Kapusta (Thales SIX (ThereSIS))