Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8552
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAbdulhamid, Shafi’i Muhammad-
dc.contributor.authorUsman, Mubaraq Olamide-
dc.contributor.authorOjerinde, Oluwaseun A.-
dc.contributor.authorVictor Ndako, Adama-
dc.contributor.authorAlhassan, John K-
dc.date.accessioned2021-07-11T17:24:59Z-
dc.date.available2021-07-11T17:24:59Z-
dc.date.issued2018-03-06-
dc.identifier.citationhttps://doi.org/10.26634/jcom.6.3.15696en_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/8552-
dc.description.abstractPhishing is a cybercrime that is described as an art of cloning a web page of a legitimate company with the aim of obtaining confidential data of unsuspecting internet users. Recent researches indicates that a number of phishing detection algorithms have been introduced into the cyber space, however, most of them depend on an existing blacklist or whitelist for classification. Therefore, when a new phishing web page is introduced, the detection algorithms find it difficult to correctly classifies it as phishy. In this paper, we put forward a soft computing approach called Artificial Neural Network (ANN) algorithm with confusion matrix analysis for the detection of e-banking phishing websites. The proposed ANN algorithm produces a remarkable percentage accuracy and reduced false positive rate during detection. This shows that, the ANN algorithm with confusion matrix analysis can produce a competitive results that is suitable for detecting phishing in e-banking websites.en_US
dc.language.isoenen_US
dc.publisherJournal on Computer Scienceen_US
dc.subjectWebsitesen_US
dc.subjectSoft Computingen_US
dc.subjectE-bankingen_US
dc.subjectArtificial Neural Networken_US
dc.subjectPhishingen_US
dc.subjectIntelligent Algorithmen_US
dc.titleA Soft Computing Approach to Detecting E-Banking Phishing Websites using Artificial Neural Network with Confusion Matrixen_US
dc.typeArticleen_US
Appears in Collections:Cyber Security Science

Files in This Item:
File Description SizeFormat 
16.pdfA Soft Computing Approach to Detecting E-Banking Phishing Websites using Artificial Neural Network with Confusion Matrix1.1 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.