Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2090
Title: NoFish; Total Anti-Phishing Protection System
Authors: Pabasara, R. A. H. D
Atimorathanna, D. N
Ranaweera, T. S
Perera, J. R
Keywords: cyber-attack
anti-phishing
information security
machine learning
visual similarity
feature extraction
natural language processing
Issue Date: 5-Dec-2020
Publisher: Global Journals
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
Series/Report no.: Global Journal of Computer Science and Technology;Vol 20, No 3-E (2020)
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.
URI: http://rda.sliit.lk/handle/123456789/2090
ISSN: 0975-4172
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - SLIIT Staff Publications

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