An Unsupervised Anomaly Detection Framework for Multiple-connection Based Network Intrusions.ET C A L I B ~ &RIQUEMENTET C A L I B ~&RIQUEMENT.POMPES PAR TRANSITIONS MULTIPLES

منو

" An Unsupervised Anomaly Detection Framework for Multiple-connection Based Network Intrusions.ET C A L I B ~ &RIQUEMENTET C A L I B ~&RIQUEMENT.POMPES PAR TRANSITIONS MULTIPLES "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	155147
Doc. No	:	ET26939
Main Entry	:	Wei Lu
Title Proper	:	An Unsupervised Anomaly Detection Framework for Multiple-connection Based Network Intrusions.ET C A L I B ~ RIQUEMENTET C A L I B ~RIQUEMENT.POMPES PAR TRANSITIONS MULTIPLES
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	In this dissertation, we propose an effective and efficient online unsupervised anomalydetection framework. The framework consists of new anomalousness metrics, named IPWeight, and a new hybrid clustering algorithm, named I-means. IP Weight metrics.
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL51218.pdf
Title and statement of responsibility and	:	An Unsupervised Anomaly Detection Framework for Multiple-connection Based Network Intrusions.ET C A L I B ~ RIQUEMENTET C A L I B ~RIQUEMENT.POMPES PAR TRANSITIONS MULTIPLES [Thesis]