URL phishing detection using machine learning

Phishing attacks have become increasingly common in recent years, with cybercriminals using a variety of techniques to trick unsuspecting victims into providing sensitive information such as login credentials or financial data. One of the most common methods of phishing is through the use of URLs, w...

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Bibliographic Details
Main Authors: Pallaiyah, Solainayagi, Amir, Mohd, Mathew, Irine Sarah, Varma, Sangaraju Sreekanth, Shakeer, Shaik, Rajendran, Mohanapriya, Govindaraj, Jijina
Format: Conference Proceeding
Language:English
Subjects:
Access control
Algorithms
Machine learning
Phishing
State-of-the-art reviews
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Summary:Phishing attacks have become increasingly common in recent years, with cybercriminals using a variety of techniques to trick unsuspecting victims into providing sensitive information such as login credentials or financial data. One of the most common methods of phishing is through the use of URLs, where attackers create fake web pages that mimic legitimate sites and use them to steal information from users to combat this threat, researchers and security experts have turned to machine learning techniques to develop algorithms that can accurately detect phishing URLs. In this paper, review the current state of the art in URL phishing detection using machine learning, including the various approaches and algorithms that have been developed.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0193960