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https://rda.sliit.lk/handle/123456789/2090
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DC Field | Value | Language |
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dc.contributor.author | Pabasara, R. A. H. D | - |
dc.contributor.author | Atimorathanna, D. N | - |
dc.contributor.author | Ranaweera, T. S | - |
dc.contributor.author | Perera, J. R | - |
dc.date.accessioned | 2022-04-28T10:54:53Z | - |
dc.date.available | 2022-04-28T10:54:53Z | - |
dc.date.issued | 2020-12-05 | - |
dc.identifier.citation | Pabasara, 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/1984 | en_US |
dc.identifier.issn | 0975-4172 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/2090 | - |
dc.description.abstract | Phishing 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.iso | en | en_US |
dc.publisher | Global Journals | en_US |
dc.relation.ispartofseries | Global Journal of Computer Science and Technology;Vol 20, No 3-E (2020) | - |
dc.subject | cyber-attack | en_US |
dc.subject | anti-phishing | en_US |
dc.subject | information security | en_US |
dc.subject | machine learning | en_US |
dc.subject | visual similarity | en_US |
dc.subject | feature extraction | en_US |
dc.subject | natural language processing | en_US |
dc.title | NoFish; Total Anti-Phishing Protection System | en_US |
dc.type | Article | en_US |
Appears in Collections: | Research Papers - Dept of Computer Systems Engineering Research Papers - SLIIT Staff Publications |
Files in This Item:
File | Description | Size | Format | |
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document (2).pdf | 584.04 kB | Adobe PDF | View/Open |
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