Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing

A deep reinforcement learning-based vehicle selection scheme is proposed to enhance the safety and accuracy of asynchronous federated learning in vehicular edge computing by considering vehicle mobility, computational resources, data size, time-varying channel conditions, and Byzantine attacks.