Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey. (arXiv:2312.08667v1 [cs.CR])

Due to the greatly improved capabilities of devices, massive data, and
increasing concern about data privacy, Federated Learning (FL) has been
increasingly considered for applications to wireless communication networks
(WCNs). Wireless FL (WFL) is a distributed method of training a global deep
learning model in which a large number of participants each train a local model
on their training datasets and then upload the local model updates to a central
server. However, in general, non-independent and identically distributed
(non-IID) data …

applications attacks backdoor backdoor attacks capabilities communication communication networks data data privacy defense devices distributed federated federated learning global networks poisoning privacy survey training wireless