Byzantine-Robust Federated Learning Framework via a Server-Client Defense Mechanisms
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3568443
Abstract: Federated learning (FL), a distributed machine learning (ML) framework, is susceptible to Byzantine attacks since the attacker can manipulate clients’ local data or models to compromise the performance of the global model. There has been… read more here.
Keywords: framework; byzantine attacks; client; byzantine ... See more keywords
Byzantine-Resilient Impulsive Control for Bipartite Consensus of Heterogeneous Multiagent Systems
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DOI: 10.1109/tcsi.2024.3517329
Abstract: This paper investigates the bipartite consensus problem for heterogeneous multi-agent systems subjected to Byzantine attacks. Byzantine agents send erroneous signals to their neighbors while utilizing incorrect input signals themselves, posing significant challenges for defense. To… read more here.
Keywords: consensus; byzantine attacks; impulsive control; bipartite consensus ... See more keywords
Anti-Byzantine attacks enabled vehicle selection for asynchronous federated learning in vehicular edge computing
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DOI: 10.23919/jcc.fa.2023-0718.202408
Abstract: In vehicle edge computing (VEC), asynchronous federated learning (AFL) is used, where the edge receives a local model and updates the global model, effectively reducing the global aggregation latency. Due to different amounts of local… read more here.
Keywords: vehicle; edge computing; asynchronous federated; byzantine attacks ... See more keywords