Toward robust hierarchical federated learning in internet of vehicles
The rapid growth of the Internet of Vehicles (IoV) paradigm sparks the generation of large
volumes of distributed data at vehicles, which can be harnessed to build models for …
volumes of distributed data at vehicles, which can be harnessed to build models for …
A survey of federated learning for connected and automated vehicles
Connected and Automated Vehicles (CAVs) represent a rapidly growing technology in the
automotive domain sector, offering promising solutions to address challenges such as traffic …
automotive domain sector, offering promising solutions to address challenges such as traffic …
Cybersecurity threats in connected and automated vehicles based federated learning systems
R Al Mallah, G Badu-Marfo… - 2021 IEEE Intelligent …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a machine learning technique that aims at training an algorithm
across decentralized entities holding their local data private. Wireless mobile networks allow …
across decentralized entities holding their local data private. Wireless mobile networks allow …
Federated learning for connected and automated vehicles: A survey of existing approaches and challenges
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …
(CAV), including perception, planning, and control. However, its reliance on vehicular data …
Kafkafed: Two-tier federated learning communication architecture for internet of vehicles
In the current era of the Internet of Vehicles (IoV), vehicle to vehicle data sharing can provide
customized applications for Connected and Autonomous Vehicles (CAVs). The …
customized applications for Connected and Autonomous Vehicles (CAVs). The …
Secure intrusion detection by differentially private federated learning for inter-vehicle networks
Q Xu, L Zhang, D Ou, W Yu - Transportation research record, 2023 - journals.sagepub.com
Along with providing several benefits, the unprecedented growth of connected and
automated vehicles brings worries about damaging cyber attacks. Network-based intrusion …
automated vehicles brings worries about damaging cyber attacks. Network-based intrusion …
Feel: Federated end-to-end learning with non-iid data for vehicular ad hoc networks
Recent studies have demonstrated the potentials of federated learning (FL) in achieving
cooperative and privacy-preserving data analytics. It would also be promising if FL can be …
cooperative and privacy-preserving data analytics. It would also be promising if FL can be …
A dispersed federated learning framework for 6G-enabled autonomous driving cars
Sixth-Generation (6G)-based Internet of Everything applications (eg autonomous driving
cars) have witnessed a remarkable interest. Autonomous driving cars using federated …
cars) have witnessed a remarkable interest. Autonomous driving cars using federated …
Bift: A blockchain-based federated learning system for connected and autonomous vehicles
Machine learning (ML) algorithms are essential components in autonomous driving. In most
existing connected and autonomous vehicles (CAVs), a large amount of driving data …
existing connected and autonomous vehicles (CAVs), a large amount of driving data …
Efficient asynchronous federated learning research in the internet of vehicles
Federated learning (FL) is a distributed machine learning paradigm that ensures data do not
leave local devices. Data sharing problems can be addressed by FL in untrusted …
leave local devices. Data sharing problems can be addressed by FL in untrusted …