A Hybrid Machine Learning approach for Detecting Intentional and Unintentional Insider Threats with Mitigation through Behavioral Biometrics and User Profiling Mechanism

dc.contributor.guide	Shanmugapriya D
dc.coverage.spatial	Computer Science Artificial Intelligence
dc.creator.researcher	Asha S
dc.date.accessioned	2026-02-16T09:26:36Z
dc.date.available	2026-02-16T09:26:36Z
dc.date.awarded	2026
dc.date.completed	2025
dc.date.registered	2021
dc.description.abstract	newline Available
dc.description.note
dc.format.accompanyingmaterial	CD
dc.format.dimensions	210X290
dc.format.extent	255
dc.identifier.researcherid	0000-0001-6302-1528
dc.identifier.uri	http://hdl.handle.net/10603/695970
dc.language	English
dc.publisher.institution	Department of Computer Science
dc.publisher.place	Coimbatore
dc.publisher.university	Avinashilingam Institute for Home Science and Higher Education for Women
dc.relation	135
dc.rights	university
dc.source.university	University
dc.subject.keyword	School of Physical sciences and Computational Sciences
dc.subject.keyword	Computer Science
dc.subject.keyword	Insider threat Detection, Cybersecurity, Artificial Intelligence, Intentional insider, Unintentional insider
dc.title	A Hybrid Machine Learning approach for Detecting Intentional and Unintentional Insider Threats with Mitigation through Behavioral Biometrics and User Profiling Mechanism
dc.title.alternative
dc.type.degree	Ph.D.