Summary
There is a strong upcoming need for communication and beyond technology on the 2030 horizon, with the transformations having been set in motion by 5G, and increasing expectations in society, accelerated by advancements in enabling technology, and moving toward new services and use cases. To address the demanding and diverse needs of the anticipated use cases, 6G networks must be highly programmable, exceedingly adaptable, and efficient. Nevertheless, the additional level of efficiency, programmability and flexibility will come at the expense of increasing complexity in managing and operating 6G networks. To bring this complexity under control, a paradigm shift toward complete automation of network and service management is required. However, a significant obstacle to full automation is the protection of the network services, infrastructure and data against possible cybersecurity risks introduced by the unheard-of expansion of the 6G threat landscape. ROBUST-6G aims to address these cybersecurity risks by 1) providing fundamental contributions to the development of data-driven, AI/ML-based security solutions to meet the new concerns posed by the dynamic nature of the future cyber-physical continuum 2) implementing fully autonomous zero-touch security management functionalities 3) exposing security functionalities to verticals and providing necessary data management 4) protecting AI/ML systems from security attacks and ensuring privacy of individuals whose data is used in the AI-driven systems. 5) providing secure, privacy-preserving and robust distributed intelligence with transparency enhancements by elaborating the explainability in AI/ML 6) achieving energy efficient 6G network design with green and sustainable AI methodologies 7) leveraging different sources of information, ranging from sensing, positioning to authentication, and advanced AI/ML methodologies for detection and mitigation of physical layer attacks and threats.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101139068 |
| Start date: | 01-01-2024 |
| End date: | 30-06-2026 |
| Total budget - Public funding: | 4 201 741,16 Euro - 3 999 956,00 Euro |
Cordis data
Original description
There is a strong upcoming need for communication and beyond technology on the 2030 horizon, with the transformations having been set in motion by 5G, and increasing expectations in society, accelerated by advancements in enabling technology, and moving toward new services and use cases. To address the demanding and diverse needs of the anticipated use cases, 6G networks must be highly programmable, exceedingly adaptable, and efficient. Nevertheless, the additional level of efficiency, programmability and flexibility will come at the expense of increasing complexity in managing and operating 6G networks. To bring this complexity under control, a paradigm shift toward complete automation of network and service management is required. However, a significant obstacle to full automation is the protection of the network services, infrastructure and data against possible cybersecurity risks introduced by the unheard-of expansion of the 6G threat landscape. ROBUST-6G aims to address these cybersecurity risks by 1) providing fundamental contributions to the development of data-driven, AI/ML-based security solutions to meet the new concerns posed by the dynamic nature of the future cyber-physical continuum 2) implementing fully autonomous zero-touch security management functionalities 3) exposing security functionalities to verticals and providing necessary data management 4) protecting AI/ML systems from security attacks and ensuring privacy of individuals whose data is used in the AI-driven systems. 5) providing secure, privacy-preserving and robust distributed intelligence with transparency enhancements by elaborating the explainability in AI/ML 6) achieving energy efficient 6G network design with green and sustainable AI methodologies 7) leveraging different sources of information, ranging from sensing, positioning to authentication, and advanced AI/ML methodologies for detection and mitigation of physical layer attacks and threats.Status
SIGNEDCall topic
HORIZON-JU-SNS-2023-STREAM-B-01-04Update Date
12-03-2024
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