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Lookup NU author(s): Dr Rehmat UllahORCiD
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© 2022 IEEE. The digital world is becoming increasingly interconnected and cyberattacks such as phishing are becoming more common. Fraudulent emails and bogus websites are used to obtain sensitive information from online users to obtain their personal information. Cyberattacks are becoming increasingly sophisticated, which makes detecting scam attacks more difficult. In order to detect phishing attacks accurately, a variety of approaches have been examined, including rules-based systems, lists-based systems, heuristic-based systems, and content-based systems, among others, with the most effective list-based systems and machine learning systems. Over the past couple of years, Deep Learning has proven to be one of the most effective algorithms for machine learning. Specifically, this paper explores and provides an overview of existing anti-phishing approaches, as well as how fraudulent URLs can be classified using machine learning and deep learning algorithms.
Author(s): Tareen S, Bazai SU, Ullah S, Ullah R, Marjan S, Ghafoor MI
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 3rd International Informatics and Software Engineering Conference (IISEC 2022)
Year of Conference: 2022
Online publication date: 29/12/2022
Acceptance date: 02/04/2018
Publisher: IEEE
URL: https://doi.org/10.1109/IISEC56263.2022.9998205
DOI: 10.1109/IISEC56263.2022.9998205
Library holdings: Search Newcastle University Library for this item
ISBN: 9781665459952
