no code implementations • 2 May 2024 • Sonakshi Garg, Hugo Jönsson, Gustav Kalander, Axel Nilsson, Bhhaanu Pirange, Viktor Valadi, Johan Östman
FLStealth, an untargeted attack, aims at providing model updates that deteriorate the global model performance while appearing benign.
1 code implementation • 6 Jun 2023 • Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi
In this paper, we present a novel approach FedVal for both robustness and fairness that does not require any additional information from clients that could raise privacy concerns and consequently compromise the integrity of the FL system.
no code implementations • 24 Oct 2022 • Viktor Valadi, Madeleine Englund, Mark Spanier, Austin O'brien
This paper proposes and investigates a new approach for detecting and preventing several different types of poisoning attacks from affecting a centralized Federated Learning model via average accuracy deviation detection (AADD).