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1、IntrusionDetectioninComputerNetworksbyMultipleClassifierSystemsGiorgioGiacintoandFabioRoliDepartmentofElectricalandElectronicEngineering–UniversityofCagliari,ItalyPiazzaD’Armi–09123Cagliari,Italy{giacinto,roli}@diee.unica.itAbstractResearchersrecentlyproposedintrusiondetectio
2、nap-proachesbasedonpatternrecognitionalgorithmstrainedThesecurityofcomputernetworksplaysastrategiconmaliciousandnormaltrafficactivities[3-6].Thisfor-roleinmoderncomputersystems.Inordertoenforcehighmulationofintrusiondetectionproblemcombinestheprotectionlevelsagainstthreats,an
3、umberofsoftwareadvantagesofsignature-basedandanomaly-basedIDS.Ittoolsarecurrentlydeveloped.IntrusionDetectionSys-allowsdesigningdecision“boundaries”betweennormaltemsaimatdetectingintruderwhoeludedthe“firstline”andmaliciousnetworktraffic.Thankstothegeneralisa-protection.Inthis
4、paper,apatternrecognitionapproachtioncapabilityofpatternrecognitionalgorithms,itisalsotonetworkintrusiondetectionbasedonthemultipleclas-possibletodetectnewattacksthatexploitthesamevul-sifiersystemsparadigmisproposed.Thepotentialitiesofnerabilitiesofknownattacks.classifiercomb
5、inationfordatafusionandsomeopenInthispaper,anapproachtointrusiondetectioninissuesareoutlined.computernetworksbasedonmultipleclassifiersystemsisproposed.Thisapproachismotivatedbytheobservation1.Introductionthathumanexpertsusedifferentfeaturesetstodetectdifferentkindsofattacks.
6、Insection2,aformulationofNowadaysanincreasingnumberofcommercialandtheintrusiondetectionproblemasapatternrecognitionpublicservicesareofferedtroughInternet,sothatsecuritytaskisgiven.Thedatafusionapproachbasedonmultipleisbecomingoneofthekeyissues.Theso-called"attacks"classifiers
7、isillustratedinsection3,andresultsonapub-tointernetserviceprovidersarecarriedoutbyexploitinglicavailabledatasetarereportedinSection4,whereunknownweaknessesorbugsalwayscontainedinsystemconclusionsarealsodrawn.andapplicationsoftware[1-2].Computernetworksareusuallyprotectedagain
8、stattacksbyanumberofaccess2.ProblemFormulationrestrictionpoliciestha
