Identifying Phishing Attacks in Communication Networks Using Url Consistency Features

dc.authorscopusid 53864626700
dc.authorscopusid 57216320767
dc.authorscopusid 56962766700
dc.authorscopusid 6603451290
dc.authorscopusid 27467587600
dc.contributor.author Azeez,N.A.
dc.contributor.author Salaudeen,B.B.
dc.contributor.author Misra,S.
dc.contributor.author Damasevicius,R.
dc.contributor.author Maskeliunas,R.
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T15:45:56Z
dc.date.available 2024-07-05T15:45:56Z
dc.date.issued 2020
dc.department Atılım University en_US
dc.department-temp Azeez 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, Lithuania en_US
dc.description.abstract Phishing 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.citationcount 40
dc.identifier.doi 10.1504/IJESDF.2020.106318
dc.identifier.endpage 213 en_US
dc.identifier.issn 1751-911X
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-85083091281
dc.identifier.scopusquality Q3
dc.identifier.startpage 200 en_US
dc.identifier.uri https://doi.org/10.1504/IJESDF.2020.106318
dc.identifier.volume 12 en_US
dc.institutionauthor Mısra, Sanjay
dc.language.iso en en_US
dc.publisher Inderscience Publishers en_US
dc.relation.ispartof International Journal of Electronic Security and Digital Forensics en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 47
dc.subject Cybersecurity en_US
dc.subject Digital evidence en_US
dc.subject Digital forensics en_US
dc.subject Phishing attacks en_US
dc.subject Risk assessment en_US
dc.title Identifying Phishing Attacks in Communication Networks Using Url Consistency Features en_US
dc.type Article en_US
dspace.entity.type Publication
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relation.isAuthorOfPublication.latestForDiscovery 53e88841-fdb7-484f-9e08-efa4e6d1a090
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relation.isOrgUnitOfPublication.latestForDiscovery e0809e2c-77a7-4f04-9cb0-4bccec9395fa

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