Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1562
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: Cyber-attack
Anti-phishing
Information Security
Machine Learning
Visual similarity
Feature extraction
Natural Language Processing
Issue Date: 10-Dec-2020
Publisher: 2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT
Series/Report no.: Vol.1;
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/123456789/1562
ISBN: 978-1-7281-8412-8
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020
Department of Computer Systems Engineering-Scopes

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