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AMPPERE : A Universal Abstract Machine for Privacy-Prese..:
, In:
Proceedings of the 30th ACM International Conference on Information & Knowledge Management
,
Yao, Yixiang
;
Ghai, Tanmay
;
Ravi, Srivatsan
. - p. 2394-2403 , 2021
Link:
https://dl.acm.org/doi/10.1145/3459637.3482318
RT T1 <cTitle>Proceedings of the 30th ACM International Conference on Information & Knowledge Management</cTitle>: T1 <Title>AMPPERE : A Universal Abstract Machine for Privacy-Preserving Entity Resolution Evaluation</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3482318&Exemplar=1&LAN=DE A1 Yao, Yixiang A1 Ghai, Tanmay A1 Ravi, Srivatsan A1 Szekely, Pedro PB ACM YR 2021 K1 abstract machine K1 entity resolution K1 homomorphic encryption K1 privacy-preserving technique K1 secure multi-party computation K1 Information systems K1 Data management systems K1 Information integration K1 Entity resolution K1 Security and privacy K1 Security services K1 Privacy-preserving protocols K1 Deduplication SP 2394 OP 2403 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3459637.3482318 DO https://dl.acm.org/doi/10.1145/3459637.3482318 SF ELIB - SuUB Bremen
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