Resource Allocation, Poisoning Attacks and Defense Strategies in Privacy-Preserving Federated Learning

Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/164251

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DC Field	Value	Language
dc.creator	Jingjing Zheng
dc.date.accessioned	2025-11-09T07:18:04Z	-
dc.date.available	2025-11-09T07:18:04Z	-
dc.date.issued	2024-10-09
dc.date.submitted	2024-12-17
dc.identifier.other	sigarra:700745
dc.identifier.uri	https://hdl.handle.net/10216/164251	-
dc.language.iso	eng
dc.rights	openAccess
dc.subject	Engenharia electrotécnica, electrónica e informática
dc.subject	Electrical engineering, Electronic engineering, Information engineering
dc.title	Resource Allocation, Poisoning Attacks and Defense Strategies in Privacy-Preserving Federated Learning
dc.type	Tese
dc.contributor.uporto	Faculdade de Engenharia
dc.identifier.doi	10.34626/wmd6-tz54
dc.identifier.tid	101804326
dc.subject.fos	Ciências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fos	Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
thesis.degree.discipline	Programa Doutoral em Engenharia Electrotécnica e de Computadores
thesis.degree.grantor	Faculdade de Engenharia
thesis.degree.grantor	Universidade do Porto
thesis.degree.level	2
Appears in Collections:	FEUP - Tese

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