TY - GEN
T1 - CROSS-FLUX
T2 - 16th International Conference on Network of the Future, NoF 2025
AU - Boualouache, Abdelwahab
AU - Silva, Vinicius F.
AU - Tang, Qiang
AU - Pardo, Enric
AU - Cherrier, Sylvain
AU - Bousalem, Badre
AU - Faye, Sebastien
AU - Langar, Rami
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In this demo paper, we present CROSS-FLUX, a novel cross-border, semi-virtualized platform designed to integrate real-world testing environments with advanced 5G vehicular network simulations for cutting-edge cybersecurity research. CROSS-FLUX enables the development, testing, and validation of network security solutions by simulating complex 5G vehicle-to-everything (V2X) use-cases involving vehicle communications across borders. The platform is particularly suited for simulating large-scale attacks involving numerous V2X nodes and collecting datasets to develop machine learning (in particular, deep learning) based intrusion detection systems. Our demo highlights its capability in detecting denial of service attacks, showcasing the platform's ability to combine a real testbed and simulations to comprehensively analyze real-world and simulated network behaviors under various cyberattack scenarios. Using two open-core network implementations to represent different mobile network operators (MNOs), CROSS-FLUX demonstrates seamless interoperability across MNOs in cross-border contexts. This flexible, scalable, and realistic platform facilitates advanced research into vehicular network security and cross-border communication resilience, providing a robust foundation for evaluating security solutions in increasingly complex and interconnected environments.
AB - In this demo paper, we present CROSS-FLUX, a novel cross-border, semi-virtualized platform designed to integrate real-world testing environments with advanced 5G vehicular network simulations for cutting-edge cybersecurity research. CROSS-FLUX enables the development, testing, and validation of network security solutions by simulating complex 5G vehicle-to-everything (V2X) use-cases involving vehicle communications across borders. The platform is particularly suited for simulating large-scale attacks involving numerous V2X nodes and collecting datasets to develop machine learning (in particular, deep learning) based intrusion detection systems. Our demo highlights its capability in detecting denial of service attacks, showcasing the platform's ability to combine a real testbed and simulations to comprehensively analyze real-world and simulated network behaviors under various cyberattack scenarios. Using two open-core network implementations to represent different mobile network operators (MNOs), CROSS-FLUX demonstrates seamless interoperability across MNOs in cross-border contexts. This flexible, scalable, and realistic platform facilitates advanced research into vehicular network security and cross-border communication resilience, providing a robust foundation for evaluating security solutions in increasingly complex and interconnected environments.
KW - 5G-V2X
KW - Cross-border
KW - Cybersecurity
KW - Hybrid platform
UR - https://www.scopus.com/pages/publications/105024949914
U2 - 10.1109/NoF66640.2025.11223297
DO - 10.1109/NoF66640.2025.11223297
M3 - Contribution to conference proceedings
AN - SCOPUS:105024949914
T3 - Proceedings of the 16th International Conference on Network of the Future, NoF 2025
SP - 111
EP - 113
BT - Proceedings of the 16th International Conference on Network of the Future, NoF 2025
A2 - Naboulsi, Diala
A2 - Wauters, Tim
A2 - Tsiropoulou, Eirini Eleni
A2 - Jimenez, Jaime Galan
A2 - Nguyen, Thi-Mai-Trang
A2 - Rovedakis, Stephane
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 30 September 2025 through 3 October 2025
ER -