Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning

arXiv:2404.06230v1 Announce Type: new
Abstract: Federated learning (FL) has been introduced to enable a large number of clients, possibly mobile devices, to collaborate on generating a generalized machine learning model thanks to utilizing a larger number of local samples without sharing to offer certain privacy to collaborating clients. However, due to the participation of a large number of clients, it is often difficult to profile and verify each client, which leads to a security threat that malicious participants may hamper …

abstract arxiv cs.cr cs.dc cs.lg devices federated learning generalized hybrid machine machine learning machine learning model mobile mobile devices network privacy pruning samples type