Intelligent orchestrated security and privacy-aware slicing for 5G and beyond vehicular networks – 5G-INSIGHT
Network slicing is considered as the key technology of an agile Vehicle-to-everything use-case deployment. However, most deployments in Europe focus on evaluating the network performance and ignore the security and privacy aspects, notably in a cross-border scenario. Building on key 5G technologies (SDN, NFV) and machine learning algorithms (federated and deep learning), 5G-INSIGHT aims at: (a) proposing new techniques for traffic prediction, thus allowing the early detection of intrusions and anomalies within 5G vehicular slices; (b) enforcing security-by design and privacy-preserving slicing policies for attack mitigation and personal data anonymization, respectively; and (c) developing resource orchestration and management across multiple potential providers using federated slicing. Proposed approaches will be validated by simulations as well as by an experimental platform (proof-of-concept) that integrates the specific characteristics of the France-Luxembourg cross-border area.
Project coordination
Rami Langar (Laboratoire d'Informatique Gaspard-Monge)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
					
						
							LIGM Laboratoire d'Informatique Gaspard-Monge
						
					
						
							DRIVE DÉPARTEMENT DE RECHERCHE EN INGÉNIÉRIE  DES VÉHICULES POUR L'ENVIRONNEMENT - EA 1859
						
					
						
							EA2118 LABORATOIRE INFORMATIQUE IMAGE INTERACTION
						
					
						
							 Luxembourg Institut of Science and Technology (LIST) / ...
						
					
						
							Uni.lu University of Luxembourg / SECAN Lab
						
					
				
				
					Help of the ANR 631,800 euros
				
				Beginning and duration of the scientific project:
					
						- 36 Months