Closing the Loophole: Rethinking Reconstruction Attacks in Federated Learning from a Privacy Standpoint

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dc.contributor.authorNa, Seung Hoko
dc.contributor.authorHong, Hyeong Gwonko
dc.contributor.authorKim, Junmoko
dc.contributor.authorShin, Seungwonko
dc.date.accessioned2022-11-24T23:00:23Z-
dc.date.available2022-11-24T23:00:23Z-
dc.date.created2022-11-19-
dc.date.issued2022-12-
dc.identifier.citationAnnual Computer Security Applications Conference, ACSAC 2022-
dc.identifier.urihttp://hdl.handle.net/10203/300925-
dc.languageEnglish-
dc.publisherACSAC-
dc.titleClosing the Loophole: Rethinking Reconstruction Attacks in Federated Learning from a Privacy Standpoint-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameAnnual Computer Security Applications Conference, ACSAC 2022-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationAT&T Conference Center, Austin, Texas-
dc.contributor.localauthorKim, Junmo-
dc.contributor.localauthorShin, Seungwon-
dc.contributor.nonIdAuthorNa, Seung Ho-
dc.contributor.nonIdAuthorHong, Hyeong Gwon-
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EE-Conference Papers(학술회의논문)
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