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PROFL: A Privacy-Preserving Federated Learning Method with ..:
, In:
2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
,
Zhong, Yisheng
;
Wang, Li-Ping
- p. 260-265 , 2024
Link:
https://doi.org/10.1109/CSCWD61410.2024.10580526
RT T1 <cTitle>2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)</cTitle>: T1 <Title>PROFL: A Privacy-Preserving Federated Learning Method with Stringent Defense Against Poisoning Attacks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10580526&Exemplar=1&LAN=DE A1 Zhong, Yisheng A1 Wang, Li-Ping YR 2024 SN 2768-1904 K1 Privacy K1 Data privacy K1 Costs K1 Federated learning K1 Interference K1 Resists K1 Robustness K1 Federated Learning K1 Poisoning Attack K1 PrivacyPreserving K1 Defense Strategy SP 260 OP 265 LK http://dx.doi.org/https://doi.org/10.1109/CSCWD61410.2024.10580526 DO https://doi.org/10.1109/CSCWD61410.2024.10580526 SF ELIB - SuUB Bremen
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