Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2090
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dc.contributor.authorPabasara, R. A. H. D-
dc.contributor.authorAtimorathanna, D. N-
dc.contributor.authorRanaweera, T. S-
dc.contributor.authorPerera, J. R-
dc.date.accessioned2022-04-28T10:54:53Z-
dc.date.available2022-04-28T10:54:53Z-
dc.date.issued2020-12-05-
dc.identifier.citationPabasara, Dhanushka Niroshan Atimorathanna, Tharindu Shehan Ranaweera, Jayani Rukshila Perera, R. (2020). NoFish; Total Anti-Phishing Protection System. Global Journal Of Computer Science And Technology, . Retrieved from https://computerresearch.org/index.php/computer/article/view/1984en_US
dc.identifier.issn0975-4172-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2090-
dc.description.abstractPhishing attacks have been identified by researchers as one of the major cyber-attack vectors which the general public has to face today. Although software companies launch new anti-phishing products, these products cannot prevent all the phishing attacks. The proposed solution, “No Fish” is a total anti-phishing protection system created especially for end-users as well as for organizations.In this paper, a realtime anti-phishing system, which has been implemented using four main phishing detection mechanisms, is proposed. The system has the following distinguishing properties from related studies in the literature: language independence, use of a considerable amount of phishing and legitimate data, real-time execution, detection of new websites, detecting zero-hour phishing attacks and use of feature-rich classifiers, visual image comparison, DNS phishing detection, email client plug in and specially the overall system has designed to the levelbased security architecture to reduce the time-consumption.en_US
dc.language.isoenen_US
dc.publisherGlobal Journalsen_US
dc.relation.ispartofseriesGlobal Journal of Computer Science and Technology;Vol 20, No 3-E (2020)-
dc.subjectcyber-attacken_US
dc.subjectanti-phishingen_US
dc.subjectinformation securityen_US
dc.subjectmachine learningen_US
dc.subjectvisual similarityen_US
dc.subjectfeature extractionen_US
dc.subjectnatural language processingen_US
dc.titleNoFish; Total Anti-Phishing Protection Systemen_US
dc.typeArticleen_US
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - SLIIT Staff Publications

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