FLoomChecker: Repelling Free-riders in Federated Learning via Training Integrity Verification

Federated learning is a mechanism that allows participating clients to train locally with their own data in order to receive rewards, thus avoiding the transfer of data to a central server and protecting users' privacy. However, some "lazy" clients may adopt the strategy of fabricatin...

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Vydané v:	Proceedings - International Conference on Parallel and Distributed Systems s. 194 - 201
Hlavní autori:	Liang, Guanghao, Chang, Shan, Dai, Minghui, Zhu, Hongzi
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 10.10.2024
Predmet:	Bloom filter Computational modeling Data models Data privacy Federated learning Filters Free-rider attack Servers TEE Training Training data Training integrity verification
ISSN:	2690-5965
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