A hybrid approach for outlier detection in MANETs using data mining techniques

dc.contributor.guide	Garg, Kanwal
dc.coverage.spatial	Computer Science and Applications
dc.creator.researcher	Popli, Renu
dc.date.accessioned	2019-04-09T05:53:09Z
dc.date.available	2019-04-09T05:53:09Z
dc.date.awarded	nd
dc.date.completed	2018
dc.date.registered	nd
dc.description.abstract	not available
dc.description.note	Bibliography p. 115-129
dc.format.accompanyingmaterial	None
dc.format.dimensions	-
dc.format.extent	156 p.
dc.identifier.uri	http://hdl.handle.net/10603/237809
dc.language	English
dc.publisher.institution	Department of Computer Sc. and Appl.
dc.publisher.place	Kurukshetra
dc.publisher.university	Kurukshetra University
dc.relation	-
dc.rights	university
dc.source.inflibnet	INFLIBNET
dc.subject.keyword	Data Mining Techniques
dc.subject.keyword	Engineering and Technology,Computer Science,Computer Science Artificial Intelligence
dc.subject.keyword	MANET Architecture
dc.subject.keyword	Outlier Detection
dc.title	A hybrid approach for outlier detection in MANETs using data mining techniques
dc.title.alternative
dc.type.degree	Ph.D.