Identifying Phishing Attacks in Communication Networks Using Url Consistency Features

dc.authoridMaskeliunas, Rytis/0000-0002-2809-2213
dc.authoridMisra, Sanjay/0000-0002-3556-9331
dc.authorwosidDamaševičius, Robertas/E-1387-2017
dc.authorwosidMaskeliunas, Rytis/J-7173-2017
dc.authorwosidMisra, Sanjay/K-2203-2014
dc.contributor.authorAzeez, Nureni Ayofe
dc.contributor.authorSalaudeen, Balikis Bolanle
dc.contributor.authorMisra, Sanjay
dc.contributor.authorDamasevicius, Robertas
dc.contributor.authorMaskeliunas, Rytis
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-10-06T10:58:13Z
dc.date.available2024-10-06T10:58:13Z
dc.date.issued2020
dc.departmentAtılım Universityen_US
dc.department-temp[Azeez, Nureni Ayofe; Salaudeen, Balikis Bolanle] Univ Lagos, Dept Comp Sci, Lagos, Nigeria; [Misra, Sanjay] Covenant Univ, Dept Elect & Informat Engn, Ota, Nigeria; [Misra, Sanjay] Atilim Univ, Dept Comp Engn, Ankara, Turkey; [Damasevicius, Robertas; Maskeliunas, Rytis] Kaunas Univ Technol, Fac Informat, Kaunas, Lithuaniaen_US
dc.descriptionMaskeliunas, Rytis/0000-0002-2809-2213; Misra, Sanjay/0000-0002-3556-9331en_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.en_US
dc.description.woscitationindexEmerging Sources Citation Index
dc.identifier.citationcount21
dc.identifier.endpage213en_US
dc.identifier.issn1751-911X
dc.identifier.issn1751-9128
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ3
dc.identifier.startpage200en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14411/8875
dc.identifier.volume12en_US
dc.identifier.wosWOS:000523687100004
dc.institutionauthorMısra, Sanjay
dc.language.isoenen_US
dc.publisherinderscience Enterprises Ltden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectphishing attacksen_US
dc.subjectrisk assessmenten_US
dc.subjectcybersecurityen_US
dc.subjectdigital forensicsen_US
dc.subjectdigital evidenceen_US
dc.titleIdentifying Phishing Attacks in Communication Networks Using Url Consistency Featuresen_US
dc.typeArticleen_US
dc.wos.citedbyCount22
dspace.entity.typePublication
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