決策樹(shù)技術(shù)及其在攻擊檢測(cè)中的應(yīng)用.pdf

1、南京理工大學(xué)碩士學(xué)位論文決策樹(shù)技術(shù)及其在攻擊檢測(cè)中的應(yīng)用姓名：張泓申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：計(jì)算機(jī)技術(shù)指導(dǎo)教師：李千目王紹良20080501Abstract碩士學(xué)位論文AbstractThenetworktechnologiesdevelopfastandtherearethekindsoftheattacktechnologies，SOthetraditionalattackdetectiontechnologiescall’tsati

2、sfyneedsoftheattackdetectionThenewattackdetectiontechnologiesmustbeappliedtOattackdetectionforadaptingthechanges，Thedecisiontreehasadvantagesofsimplestructure，wellunderstanding，highprecisionandn0parameters，SOthisdisserta

3、tionappliedthedecisiontreetoattackdetectionInthisdissertation，whenweseJeclattributesfordeciosintree，wcselecttheattributeswhosecorrelationjSthemaximalbetweenitsfatherattributeTheexperimentprovesthatitincreasesthedetection

4、ratioTheapplicationofdataminingtechnologytoanomalydetectionsystemofmobileAdHoenetworksisproposedThrough‘pointingoutitsexistingproblems，itisproposedthattheoutlierdataminingtechnologyisusedinmobileAdHoenetworkanomalydetect

5、ionsystem，Itscoreideaisthattheanomalyintrusiondetectionprocesswillbeseenasacombinationofknowledgeinthefieldofdataanalysisprocess，theintroductionofoutlierdataminingtechnologyInviewoftheexistinganomalydetectionalgorithmwhi

6、chappliestoonlydimensionofthedataset|owerreal—timedifferencehighrateoffalsepositives，theabilitytodefectnewtylⅪ$ofattacks，OutlierdataminingtechnologyisdesignedtosolvetheexistingproblemsinthemobileAdHoenetworksanomalyintru

7、siondetectionsystem，andtheworkingprincipleandsystemarchitectureisputforward，thefunctionofeachmoduleisgivenadetailedexplanationFinallyalargeamountexperimentsOnDARPAWascarriedoutandthevalidationandeffectivenessofOarapproac