A Review of Methods for Phishing Website Detection from Legal websites

Document Type : Original Article

Authors

1 Engineering Department, Imam Khomeini International University, Qazvin, Iran

2 Engineering department, imam khomeini international university, qazvin, iran

Abstract

The increasing popularity of the Internet has led to the dramatic growth of e-commerce. However, such activities have significant security challenges, mainly due to cyber fraud and identity theft. Therefore, checking the legitimacy of visited web pages is a very important task to secure the identity of customers and prevent phishing attacks. The use of machine learning methods, and deep learning is widely recognized as a promising solution. Research is full of studies that use machine learning and deep learning methods to detect website phishing. However, their findings depend on the data set and are far from generalizable. The two main reasons for the lack of generalization are impractical replication and lack of appropriate benchmark data sets for fair evaluation of systems. Furthermore, phishing methods are constantly evolving and the proposed models do not keep up with the rapid changes. In this article, we review the methods of identifying phishing sites from legal sites and finally reach the final conclusion.

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References

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Applied and basic Machine intelligence research
Volume 1, Issue 2
December 2023
Pages 44-53

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