… Byzantine-robust federated learning (… poisoning attacks to Byzantine-robust federated
learning. Existing studies [9, 66] only showed local model poisoning attacks to federated learning …

… , label flipping attacks become a feasible strategy to implement data poisoning, attacks which
… We demonstrate our FL poisoning attacks using two popular image classification datasets: …

… Federated learning (FL) has recently emerged as a … major attacks on FL: 1) poisoning attacks
and 2) inference attacks, … assumptions adopted by various attacks, and discuss promising …

… federated learning intuitively. In this paper, through real implementation of a federated learning
system and distributed poisoning attacks… poisoned training samples, attackers, and attack …

… To obtain a fair understanding of the defenses’ performance under a more realistic setting,
we adopt a federated learning system with 100 clients and the MNIST dataset with 10 classes, …

… federated learning systems that involve millions of clients. In this work, we propose the first
Model Poisoning Attack … injects fake clients to a federated learning system and sends carefully …

… Learning (ML) technique to keep the local data private, it is also vulnerable to attacks like …
the FL domain, this report discusses the opportunities and challenges in federated learning. …

… • We introduce a new attack approach that circumvents IoT intrusion detection system using
Federated Learning (FL). In this attack, the attacker indirectly attacks FL-based IoT anomaly …

… during the federated training process. In this paper, we present a general framework for
model poisoning attacks on FL. We show that our framework leads to poisoning attacks that …

… variety of attacks, including model poisoning, … federated learning to sybil-based poisoning
attacks. We then describe FoolsGold, a novel defense to this problem that identifies poisoning …