Identifying phishing attacks in communication networks using URL consistency features

dc.authorscopusid53864626700
dc.authorscopusid57216320767
dc.authorscopusid56962766700
dc.authorscopusid6603451290
dc.authorscopusid27467587600
dc.contributor.authorMısra, Sanjay
dc.contributor.authorSalaudeen,B.B.
dc.contributor.authorMisra,S.
dc.contributor.authorDamasevicius,R.
dc.contributor.authorMaskeliunas,R.
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-09-10T21:35:47Z
dc.date.available2024-09-10T21:35:47Z
dc.date.issued2020
dc.departmentAtılım Universityen_US
dc.department-tempAzeez N.A., Department of Computer Sciences, University of Lagos, Lagos, Nigeria; Salaudeen B.B., Department of Computer Sciences, University of Lagos, Lagos, Nigeria; Misra S., Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria, Department of Computer Engineering, Atilim University, Ankara, Turkey; Damasevicius R., Faculty of Informatics, Kaunas University of Technology, Kaunas, Lithuania; Maskeliunas R., Faculty of Informatics, Kaunas University of Technology, Kaunas, Lithuaniaen_US
dc.description.abstractPhishing is a fraudulent attempt by cybercriminals, where the target audience is addressed by a text message, phone call or e-mail, requesting classified and sensitive information after presenting himself/herself as a legitimate agent. Successful phishing attack may result into financial loss and identity theft. Identifying forensic characteristics of phishing attack can help to detect the attack and its perpetuators and as well as to enable defence against it. To shield internet users from phishing assaults, numerous anti-phishing models have been proposed. Currently employed techniques to handle these challenges are not sufficient and capable enough. We aim at identifying phishing sites in order to guard internet users from being vulnerable to any form of phishing attacks by verifying the conceptual and literal consistency between the uniform resource locator (URL) and the web content. The implementation of the proposed PhishDetect method achieves an accuracy of 99.1%; indicating that it is effective in detecting various forms of phishing attacks. © 2020 Inderscience Enterprises Ltd.. All rights reserved.en_US
dc.identifier.citation40
dc.identifier.doi10.1504/IJESDF.2020.106318
dc.identifier.endpage213en_US
dc.identifier.issn1751-911X
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ3
dc.identifier.startpage200en_US
dc.identifier.urihttps://doi.org/10.1504/IJESDF.2020.106318
dc.identifier.urihttps://hdl.handle.net/20.500.14411/7367
dc.identifier.volume12en_US
dc.language.isoenen_US
dc.publisherInderscience Publishersen_US
dc.relation.ispartofInternational Journal of Electronic Security and Digital Forensicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCybersecurityen_US
dc.subjectDigital evidenceen_US
dc.subjectDigital forensicsen_US
dc.subjectPhishing attacksen_US
dc.subjectRisk assessmenten_US
dc.titleIdentifying phishing attacks in communication networks using URL consistency featuresen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication53e88841-fdb7-484f-9e08-efa4e6d1a090
relation.isAuthorOfPublication.latestForDiscovery53e88841-fdb7-484f-9e08-efa4e6d1a090
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relation.isOrgUnitOfPublication.latestForDiscoverye0809e2c-77a7-4f04-9cb0-4bccec9395fa

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