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Enhancing Internet of Things Security: Practical Solutions using Federated Learning and One-Class Classifiers

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dc.contributor.advisorMakaroff, Dwight
dc.contributor.committeeMemberEager, Derek
dc.contributor.committeeMemberStakhanova, Natalia
dc.contributor.committeeMemberBui, Francis
dc.contributor.committeeMemberNikolaidis, Ioanis
dc.contributor.committeeMemberMcQuillan, Ian
dc.creatorGolestani Najafabadi, Shahrzad
dc.creator.orcid0009-0008-3198-3034
dc.date.accessioned2024-09-25T20:28:55Z
dc.date.copyright2024
dc.date.created2024-08
dc.date.issued2024-09-25
dc.date.submittedAugust 2024
dc.date.updated2024-09-25T20:28:56Z
dc.description.abstract
This item is under an embargo. Access to the abstract will not be permitted until 2026-09-25
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10388/16088
dc.language.isoen
dc.subjectInternet of Things (IoT)
dc.subjectIntrusion Detection System (IDS)
dc.subjectAnomaly Detection
dc.subjectFederated Learning (FL)
dc.subjectUnsupervised Learning
dc.subjectOne-Class Classifier (OCC)
dc.subjectMachine Learning (ML)
dc.subjectDeep Learning (DL)
dc.subjectDevice-Specific Models
dc.subjectDevice-Type-Specific Models.
dc.titleEnhancing Internet of Things Security: Practical Solutions using Federated Learning and One-Class Classifiers
dc.typeThesis
dc.type.materialtext
local.embargo.lift2026-09-25
local.embargo.terms2026-09-25
thesis.degree.departmentComputer Science
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Saskatchewan
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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