Using Fuzzy Sets for Detecting Cyber Terrorism and Extremism in the Text

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dc.contributor.authorNidauzel, Vahide
dc.contributor.authorSaraç Eşsiz, Esra
dc.contributor.authorAyşe Özel, Selma
dc.date.accessioned2025-01-06T17:29:43Z
dc.date.available2025-01-06T17:29:43Z
dc.date.issued2018
dc.description2018 Innovations in Intelligent Systems and Applications Conference, ASYU 2018 -- 4 October 2018 through 6 October 2018 -- Adana -- 143261
dc.description.abstractThe concept of Cyber Security (CS) has been started to be used with the development of Internet technology. Nowadays, CS has vital importance and Cyber Terror and Extremism (CTE) is one of the CS problems. Terror must be detected before terrorism comes true. In other words, people who commit the crime must be detected automatically before they move on. At this stage, what people say about some issues is very valuable because sayings can be turned into actions. The aim of this study is to use Antisocial Behavior dataset to try to detect CTE in the text contents. To detect CTE, text documents should be converted to numerical vectors which consist of numerical weights of the terms present in the text documents. Vectors are computed by using four different weighting methods in our study. These methods are the well-known binary weighting, term frequency based weighting, term frequency and inverse document frequency based weighting, and our proposed fuzzy set based weighting methods. Naive Bayes Multinomial (NBM) and Support Vector Machines (SVM) are used as classifiers to compare the performances of the weighting methods for CTE detection. Our experimental analysis shows that fuzzy set based weighting method with SVM classifier gives the best classification accuracy which reaches up to 99%. © 2018 IEEE.
dc.identifier.doi10.1109/ASYU.2018.8554017
dc.identifier.isbn978-153867786-5
dc.identifier.scopus2-s2.0-85059976322
dc.identifier.urihttps://doi.org/10.1109/ASYU.2018.8554017
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1309
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings - 2018 Innovations in Intelligent Systems and Applications Conference, ASYU 2018
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectcyber terrorism and extremism
dc.subjectfuzzy sets
dc.subjecttext classification
dc.subjectweighting methods
dc.titleUsing Fuzzy Sets for Detecting Cyber Terrorism and Extremism in the Text
dc.typeConference Object

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