Oct. 16, 2023, 1:10 a.m. | Chao Feng, Alberto Huertas Celdran, Michael Vuong, Gerome Bovet, Burkhard Stiller

cs.CR updates on arXiv.org arxiv.org

The growing concern over malicious attacks targeting the robustness of both
centralized and decentralized federated learning (FL) necessitates novel
defensive strategies. In contrast to the centralized approach, decentralized FL
(DFL) has the advantage of utilizing network topology and local dataset,
enabling the exploration of moving target defense (MTD) based approaches. This
work presents a theoretical analysis of the influence of network topology on
the rubostness of DFL models. Drawing inspiration from these findings, a
three-stage MTD-based aggregation protocol, called as …

aggregation attacks dataset decentralized defense defensive federated learning local malicious moving moving target defense network novel poisoning poisoning attacks protocol robustness strategies target targeting voyager

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