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AICHAIN

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A platform for privacy preserving Federated Machine Learning using Blockchain to...

A platform for privacy preserving Federated Machine Learning using Blockchain to enable Operational Improvements in ATM This project proposes an innovative Digital Information Management (DIM) concept, i.e. the AICHAIN solution, that aims at enabling the cyber-secured exploitation of large private data sets that belong to different stakeholders and... ver más

31/12/2022

SITA EWAS APPLICAT...

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

SITA EWAS APPLICATION SERVICES SL No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-12-31

SESAR-ER4-04-2019: Digital Information Management

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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7 Participantes

SITA EWAS APPLICATION SERVIC...

283.41K€ | Lider

IQC GmbH

289.82K€ | Participante

SITA INFORMATION NETWORKING...

36.25K€ | Participante

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Duración del proyecto: 31 meses Fecha Inicio: 2020-05-15
Fecha Fin: 2022-12-31

Líder del proyecto

SITA EWAS APPLICATION SERVICES SL No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto This project proposes an innovative Digital Information Management (DIM) concept, i.e. the AICHAIN solution, that aims at enabling the cyber-secured exploitation of large private data sets that belong to different stakeholders and that contain valuable information for ATM operations. To overcome the stakeholders’ reluctance to share sensitive data, the exploitation will not be performed by exchanging the data itself but by articulating an advanced privacy-preserving federated learning architecture in which neither the training data nor the training model need to be exposed. This will be possible thanks to the innovative combination of two emerging DIM technologies: Federated Machine Learning (FedML) and Blockchain technologies. The potential benefits of the new proposed DIM concept will be explored through ATM research use cases related to advanced Demand Capacity Balancing (DCB) predictive models of the Network Manager (NM), whose prediction performance is expected to significantly improve thanks to the exploitation of relevant operational private data from Airspace Users. The accuracy of the new DCB predictive models augmented with real operational data accessed through the AICHAIN solution will be benchmarked against the machine learning models for DCB that are currently in use or under research by NM. The project will also address the exploration of governance and incentives mechanisms as part of the AICHAIN solution concept architecture, to facilitate the adoption of the concept and the alignment of interests of the key stakeholders (especially of the data owners). The design of advanced governance & incentives mechanisms, which could be implemented using the mechanism of smart contracts available in the toolset of Blockchain, will be complemented with a theoretical identification of data exploitation benefits and with discussions in workshops participated by external experts.

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