Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2082
Title: NoFish; total anti-phishing protection system
Authors: Atimorathanna, D. N
Ranaweera, T. S
Pabasara, R. A. H. D
Perera, J. R
Abeywardena, K. Y
Keywords: NoFish
Total Anti-Phishing
Protection System
Issue Date: 10-Dec-2020
Publisher: IEEE
Citation: D. Niroshan Atimorathanna, T. Shehan Ranaweera, R. A. H. Devdunie Pabasara, J. Rukshila Perera and K. Yapa Abeywardena, "NoFish; Total Anti-Phishing Protection System," 2020 2nd International Conference on Advancements in Computing (ICAC), 2020, pp. 470-475, doi: 10.1109/ICAC51239.2020.9357145.
Series/Report no.: 2020 2nd International Conference on Advancements in Computing (ICAC);Vol. 1 Pages 470-475
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 many vendors constantly launch new anti-phishing products, these products cannot prevent all the phishing attacks. The proposed solution, “NoFish” is a total anti-phishing protection system created especially for end-users as well as for organizations. This paper proposes a machine learning & computer vision-based approach for intelligent phishing detection. 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 plugin and especially the overall system is designed using a level-based security architecture to reduce the time-consumption. Users can simply download the NoFish browser extension and email plugin to protect themselves, establishing a relatively secure browsing environment. Users are more secure in cyberspace with NoFish which depicts a 97% accuracy level.
URI: http://rda.sliit.lk/handle/123456789/2082
ISBN: 978-1-7281-8412-8
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - Open Access Research
Research Papers - SLIIT Staff Publications

Files in This Item:
File Description SizeFormat 
NoFish_Total_Anti-Phishing_Protection_System.pdf
  Until 2050-12-31
382.77 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.