activity
20172024
most citedA Survey on Machine Learning-based Misbehavior Detection Systems for 5G and Beyond Vehicular Networks

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2024

Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks

Abdelaziz Amara korba, Abdelwahab Boualouache, Bouziane Brik +3

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 contex…

cs.CR2024

Zero-X: A Blockchain-Enabled Open-Set Federated Learning Framework for Zero-Day Attack Detection in IoV

Abdelaziz Amara korba, Abdelwahab Boualouache, Yacine Ghamri-Doudane

The Internet of Vehicles (IoV) is a crucial technology for Intelligent Transportation Systems (ITS) that integrates vehicles with the Internet and other entities. The emergence of…

cs.CR2022★ 3 cited

A Survey on Machine Learning-based Misbehavior Detection Systems for 5G and Beyond Vehicular Networks

Abdelwahab Boualouache, Thomas Engel

Significant progress has been made towards deploying Vehicle-to-Everything (V2X) technology. Integrating V2X with 5G has enabled ultra-low latency and high-reliability V2X communic…

cs.CR2020

Software-Defined Location Privacy Protection for Vehicular Networks

Abdelwahab Boualouache, Ridha Soua, Thomas Engel

While the adoption of connected vehicles is growing, security and privacy concerns are still the key barriers raised by society. These concerns mandate automakers and standardizati…

cs.CR2017

A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks

Abdelwahab Boualouache, Sidi-Mohammed Senouci, Samira Moussaoui

The initial phase of the deployment of Vehicular Ad-Hoc Networks (VANETs) has begun and many research challenges still need to be addressed. Location privacy continues to be in the…