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Latent Semantic Analysis and Keyword Extraction for Phishing Classication Gast on LHuillier Latent Semantic Analysis and Keyword Extraction for Phishing Classication Gast on LHuillier

Latent Semantic Analysis and Keyword Extraction for Phishing Classication Gast on LHuillier - PDF document

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Uploaded On 2014-10-25

Latent Semantic Analysis and Keyword Extraction for Phishing Classication Gast on LHuillier - PPT Presentation

uchilecl Richard Weber Sebasti an R 305os Department of Industrial Engineering University of Chile Rep ublica 701 Santiago Chile Email rwebersrios diiuchilecl Abstract Phishing email fraud has been considered as one of the main cyberthreats over the ID: 7427

uchilecl Richard Weber Sebasti

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ORKNowadays,inthecyber-crime keepraisingastheinternetpenetrationinoureverydaylifeincreases.DifferenttextminingtechniquesforphishingÞlteringhavebeenproposed.In[1],LogisticRegression,SupportVectorMachines(SVMs),andRandomForestsareusedtoestimateclassiÞersforthecorrectlabelingofemailmessages.Byusingofmoresophisticatedtextminingtechniques,Bergholzetal.([3],[4])proposedanovelcharacterizationofemailsusingaClass-Topicmodel.Forphishingfeatureextractionseveralmethodologieshavebeendeveloped[1],[2],[4],[7],while combinationofstructuralbasicfeatures$,whichareinde-pendentfromtheothercontentbasedfeaturesset#,!and".However,thesesetsarenotindependentfromeachother.Theyarerepresentedbybinaryfeatures,indicatingwhetherakeywordortopicispresentedinagivenmessage,whoseintersectiondescribesaÞnalsetoffeaturesthatrepresentsa tiveclassiÞermodelsrepresentedbylogisticregression.ThissupportstheussualpreferenceofSVMsforclassiÞcationtasks,speciallyintext-miningapplications. GerhardPaass,andSiehyunStrobel.NewÞlteringapproachesforphishingemail.