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1
PPFL : privacy-preserving federated learning with truste..:
, In:
Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services
,
Mo, Fan
;
Haddadi, Hamed
;
Katevas, Kleomenis
... - p. 94-108 , 2021
Link:
https://dl.acm.org/doi/10.1145/3458864.3466628
RT T1 <cTitle>Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services</cTitle>: T1 <Title>PPFL : privacy-preserving federated learning with trusted execution environments</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3466628&Exemplar=1&LAN=DE A1 Mo, Fan A1 Haddadi, Hamed A1 Katevas, Kleomenis A1 Marin, Eduard A1 Perino, Diego A1 Kourtellis, Nicolas PB ACM YR 2021 K1 Security and privacy K1 Human and societal aspects of security and privacy K1 Privacy protections K1 Computing methodologies K1 Distributed computing methodologies K1 Distributed algorithms K1 Systems security K1 Distributed systems security SP 94 OP 108 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3458864.3466628 DO https://dl.acm.org/doi/10.1145/3458864.3466628 SF ELIB - SuUB Bremen
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