Search results for "V2X"
showing 6 items of 6 documents
Edge Computing-enabled Intrusion Detection for C-V2X Networks using Federated Learning
2022
Intrusion detection systems (IDS) have already demonstrated their effectiveness in detecting various attacks in cellular vehicle-to-everything (C-V2X) networks, especially when using machine learning (ML) techniques. However, it has been shown that generating ML-based models in a centralized way consumes a massive quantity of network resources, such as CPU/memory and bandwidth, which may represent a critical issue in such networks. To avoid this problem, the new concept of Federated Learning (FL) emerged to build ML-based models in a distributed and collaborative way. In such an approach, the set of nodes, e.g., vehicles or gNodeB, collaborate to create a global ML model trained across thes…
An Overview of 5G Slicing Operational Business Models for Internet of Vehicles, Maritime IoT Applications and Connectivity Solutions
2021
Identification of ecosystems and Business Models (BM) is an important starting point for new complex system development. The definition of actor (or stakeholder) roles and their interactions (at both business and technical levels), together with target scenarios and use cases, provide essential input information for further system requirement collection and architecture specification. The powerful and flexible Fifth Generation (5G) network slicing technology, which is capable of creating virtually isolated and logically parallel networks, enables a large range of complex services and vertical applications. Although various terminologies and models have been proposed in recent years for BMs …
5G Functional Architecture and Signaling Enhancements to Support Path Management for eV2X
2019
Enhanced vehicle-to-everything (eV2X) communication is one of the most challenging use cases that the fifth generation (5G) of cellular mobile communications must address. In particular, eV2X includes some 5G vehicular applications targeting fully autonomous driving which require ultra-high reliability. The usual approach to providing vehicular communication based on single-connectivity transmission, for instance, through the direct link between vehicles (PC5 interface), often fails at guaranteeing the required reliability. To solve such a problem, in this paper, we consider a scheme where the radio path followed by eV2X messages can be proactively and dynamically configured to either trans…
Collecte des données Véhicule/Environnement et remontée avec réseau Cellulaire et réseau Véhiculaire
2019
Vertical handover is one of the key technologies that will facilitate the connected and autonomous vehicles deployment. Today, the emergence of Vehicular Ad hoc Networks (VANETs): Vehicle-to-Vehicle (V2V) communications, Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) has enabled new applications such as Cooperative Intelligent Transport Systems (C-ITS), real-time applications (for example, autonomous driving), road traffic management applications and comfort applications. However, these networks are characterized by a high level of mobility and dynamic change in the topology, which generates scattered networks and requires handover mechanisms for maintaining ongoing session…
Reconstrucción del entorno radio para comunicaciones en agrupaciones de vehículos
2020
Los pelotones de vehículos son grupos de vehículos que viajan juntos, manteniendo una distancia constante entre ellos. Los pelotones suelen necesitar comunicaciones inalámbricas sólidas y fiables para mantener su estructura y realizar maniobras coordinadas. Cuando el pelotón es asistido por la infraestructura a través de una comunicación celular vehículo a todo (V2X), uno de los factores críticos es reducir la latencia de la comunicación. En este trabajo se explora el uso de una técnica de interpolación espacial, concretamente el Kriging Ordinario, como mecanismo para reducir la sobrecarga de señalización en la etapa de adquisición de información del canal, lo que puede repercutir en la prá…
Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks
2023
Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases th…