Data Mining Techniques for Effective and Scalable Traffic Analysis

Data Mining Techniques for Effective and Scalable Traffic Analysis

ID：39358304

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頁數(shù)：14頁

時間：2019-07-01

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1、DataMiningTechniquesforEffectiveandScalableTrafficAnalysisM.Baldi,E.Baralis,F.RissoDipartimentodiAutomaticaeInformatica-PolitecnicodiTorinoCorsoDucadegliAbruzzi,2410129Torino,Italy{mario.baldi,elena.baralis,fulvio.risso}@polito.itAbstractThispaperdescribesa

2、novelapproachtotrafficanalysisinhighspeednetworksbasedondataminingtechniques.Dataminingtechniquesarehereappliedasameanstoeffectivelyprocessthesignificantamountofcaptureddata.Thepaperprovidesafirstevaluationoftheproposedapproachintermsofitsabilityofextractin

3、grelevantinformationanditscomputationalrequirements.Suchevaluationisbasedonexperimentsrunonaprototypalimplementationoftheproposedapproach.KeywordsTrafficAnalysis,NetworkMonitoring,DataMining1.IntroductionOneofthemostcriticalissuesinkeepinganetworkundercontr

4、oliscapturingandanalyzingitstraffic.Thecomplexityofthesetasksisincreasingasnetworksbecomefasterandfaster.MajorproblemsstemfromtheCPUpowerneededtoprocesscapturednetworktrafficandthestoragerequirementsofhistoricaldata.Often,trafficcapturingandanalysisgoesthro

5、ughthestepsdepictedinFigure1,allofwhicharecriticalwhenoperatingathighdatarates.Somelimitedprocessing(e.g.associatingeachpackettoitscorrespondingflow)iscarriedoutinreal-timeimmediatelyduringthecapturesession.Then,resultscanbestoredonadisktobefurtherelaborate

6、dwithoff-linetools,whichdonotsufferthelimitationsstemmingfromreal-timeprocessing.Ad-hocsolutionsbasedonadvancedhardware(e.g.thenetworkinterfacecardsprovidedbyEndace[16])andtheuseofSMPworkstationsorevenclusterscanmitigatetheproblemsrelatedtoon-linemonitoring

7、andanalysis(thefirststepsinFigure1).However,nostraightforwardsolutionexiststoreducethecriticalitiesofthesubsequentsteps.Forinstance,a10Gbpspipecarriesmorethan100TBytesinthecourseofaday,whichisatremendousamountofdatatobestoredforsubsequentprocessing.Thisresu

8、ltsintwoproblems:ontheonehand,theinfrastructureneededtostoresuchamountofdataissophisticatedandcostlyand,ontheotherhand,locatingrelevantinformationwithinthesaveddataiscomputationallyintenseandtimeconsum

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