Communication Dans Un Congrès Année : 2024

ROBUST-6G: Smart, Automated, and Reliable Security Service Platform for 6G

Shen Wang
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Cem Ayyildiz
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Veli Can Yildirim
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Hakan Alakoca
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Fatma Günes Kesik
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Betül Güvenç Paltun
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Giovanni Perin
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Michele Rossi
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Stefano Tomasin
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Arsenia Chorti
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Pietro G Giardina
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Alberto García Pércz
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José María Jorquera Valero
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Tommy Svensson
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  • PersonId : 962734
Marios Kountouris
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Résumé

In the progressive development towards 6G, the ROBUST-6G initiative aims to provide fundamental contributions to developing data-driven, AI/ML-based security solutions to meet the new concerns posed by the dynamic nature of forthcoming 6G services and networks in the future cyber-physical continuum. This aim has to be accompanied by the transversal objective of protecting AI/ML systems from security attacks and ensuring the privacy of individuals whose data are used in AIempowered systems. ROBUST-6G will essentially investigate the security and robustness of distributed intelligence, enhancing privacy and providing transparency by leveraging explainable AI/ML (XAI). Another objective of ROBUST-6G is to promote green and sustainable AI/ML methodologies to achieve energy efficiency in 6G network design. The vision of ROBUST-6G is to optimize the computation requirements and minimize the consumed energy while providing the necessary performance for AI/ML-driven security functionalities; this will enable sustainable solutions across society while suppressing any adverse effects. This paper aims to initiate the discussion and to highlight the key goals and milestones of ROBUST-6G, which are important for investigation towards a trustworthy and secure vision for future 6G networks.

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Dates et versions

hal-04802891 , version 1 (25-11-2024)

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Bartlomiej Siniarski, Chamara Sandeepa, Shen Wang, Madhusaska Liyanage, Cem Ayyildiz, et al.. ROBUST-6G: Smart, Automated, and Reliable Security Service Platform for 6G. ICUFN 2024, Fifteenth International Conference on Ubiquitous and Future Networks, IEEE, Jul 2024, Budapest, Hungary. pp.384-389, ⟨10.1109/ICUFN61752.2024.10624832⟩. ⟨hal-04802891⟩

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