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Deep Tech INNOVATION
Privacy preserving machine learning platform capable of sharing knowledge from sensitive industrial data
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Market Maturity: Tech Ready
These are innovations that are progressing on technology development process (e.g. pilots, prototypes, demonstration). Learn more
Market Creation Potential
This innovation was assessed by the JRC’s Market Creation Potential indicator framework as having a Very high” level of Market Creation Potential. Only innovations that are showing multiple signals of market creation potential are assigned a value under this indicator system. Learn more
Go to Market needs
Needs that, if addressed, can increase the chances this innovation gets to (or closer to) the market incude:
  • Prepare for Market entry
  • Scale-up market opportunities
Location of Key Innovators developing this innovation
Key Innovators
UN Sustainable Development Goals(SDG)
This innovation contributes to the following SDG(s)
SUSTAINABLE DEVELOPMENT GOAL 9
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

The UN explains: "Investments in infrastructure – transport, irrigation, energy and information and communication technology – are crucial to achieving sustainable development and empowering communities in many countries. It has long been recognized that growth in productivity and incomes, and improvements in health and education outcomes require investment in infrastructure."

The EU-funded Research Project
This innovation was developed under the Horizon 2020 project MUSKETEER with an end date of 30/11/2021
  • Read more about this project on CORDIS
Description of Project MUSKETEER
The massive increase in data collected and stored worldwide calls for new ways to preserve privacy while still allowing data sharing among multiple data owners. Today, the lack of trusted and secure environments for data sharing inhibits data economy while legality, privacy, trustworthiness, data value and confidentiality hamper the free flow of data. By the end of the project, MUSKETEER aims to create a validated, federated, privacy-preserving machine learning platform tested on industrial data that is inter-operable, scalable and efficient enough to be deployed in real use cases. MUSKETEER aims to alleviate data sharing barriers by providing secure, scalable and privacy-preserving analytics over decentralized datasets using machine learning. Data can continue to be stored in different locations with different privacy constraints, but shared securely. The MUSKETEER cross-domain platform will validate progress in the industrial scenarios of smart manufacturing and health. MUSKETEER strives to (1) create machine learning models over a variety of privacy-preserving scenarios, (2) ensure security and robustness against external and internal threats, (3) provide a standardized and extendable architecture, (4) demonstrate and validate in two different industrial scenarios and (5) enhance data economy by boosting sharing across domains. The MUSKETEER impact crosses industrial, scientific, economic and strategic domains. Real-world industry requirements and outcomes are validated in an operational setting. Federated machine learning approaches for data sharing are innovated. Data economy is fostered by creating a rewarding model capable of fairly monetizing datasets according to the real data value. Finally, Europe is positioned as a leader in innovative data sharing technologies.

Innnovation Radar's analysis of this innovation is based on data collected on 24/07/2020.
The unique id of this innovation in the European Commission's IT systems is: 20185