The fuzzy common vulnerability scoring system (F-CVSS) based on a least squares approach with fuzzy logistic regression

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dc.authorid0000-0002-2914-1056en_US
dc.contributor.authorGencer, Kerem
dc.contributor.authorBaşçiftçi, F.
dc.date.accessioned2021-01-10T06:54:48Z
dc.date.available2021-01-10T06:54:48Z
dc.date.issued2020
dc.departmentKMÜ, Teknik Bilimler Meslek Yüksekokulu, Bilgisayar Programcılığı Bölümü
dc.descriptionWOS:000659938100004en_US
dc.description.abstractThis study presents a new approach for calculations within the Common Vulnerability Scoring System that scoring the effects of vulnerabilities in software on the security status. These calculations is the method that is most commonly used in scoring software vulnerabilities. The present model demonstrates how software security vulnerabilities can be calculated using linguistic terms. Therefore, the proposed method has a more flexible structure than this system. The current Common Vulnerability Scoring System formula and scores were used to assess and implement the presented model. The aim was to form a fuzzy model called the Fuzzy Common Vulnerability Scoring System based on the success probabilities which are defined using linguistic terms such as low, very low or high. Moreover, the Fuzzy Logistic Regression (FLR) method was used to define the relationship between the exact inputs and fuzzy multiple outputs, and the Least Squares Method was used to estimate the parameters of the presented model. The performance of the model was evaluated by a comparison using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Kim and Bishu's criterion. Validity of the fuzzy regression model is demonstrated with different fitness functions. The expectation was that more practical estimations with better error tolerance can be achieved by using linguistic terms to assess common vulnerabilities. © 2020en_US
dc.identifier.citationGencer, K., Başçiftçi, F. (2020). The fuzzy common vulnerability scoring system (F-CVSS) based on a least squares approach with fuzzy logistic regression. Egyptian Informatics Journal.
dc.identifier.doi10.1016/j.eij.2020.07.001
dc.identifier.endpage153en_US
dc.identifier.issn1110-8665
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85088786623
dc.identifier.scopusqualityQ1
dc.identifier.startpage145en_US
dc.identifier.urihttps://doi.org/10.1016/j.eij.2020.07.001
dc.identifier.urihttps://hdl.handle.net/11492/3983
dc.identifier.volume22en_US
dc.identifier.wosWOS:000659938100004
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakScopus
dc.institutionauthorGencer, Kerem
dc.language.isoen
dc.publisherElsevier B.V.en_US
dc.relation.journalEgyptian Informatics Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCommon Vulnerability Scoring Systemen_US
dc.subjectFuzzy Least Squaresen_US
dc.subjectFuzzy Logistic Regressionen_US
dc.subjectProbability Ratesen_US
dc.titleThe fuzzy common vulnerability scoring system (F-CVSS) based on a least squares approach with fuzzy logistic regressionen_US
dc.typeArticle

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