A Review on Phishing Website Detection Using Machine Learning Approach

Nikita Pawar and P. A. Tijare

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2023, vol. 9, issue 2, 267-272

Abstract: Phishing attacks are a rapidly growing threat in the cyber world. Every person is truly dependent on the internet. Everyone is doing online purchasing and online activities like online banking, online booking, and online billing on the internet. Phishing is a type of threat on a website and phishing is the illegal use of real information on the website information such as login id, password, information of credit card. Phishers use websites that visually and semantically resemble real websites. How can someone tell the difference between a website that is a phishing website and a real website? The identification of a website as a phishing website depends on several factors such as URL length, including the special letter '@', double slash redirect, and the existence of subdomains. Although the above factors are present on the website, no one can claim that the website is a phishing website, it can also be an original website. For solving this type of problem we can use the machine learning algorithm. The review creates phishing attack alerts, detects the attack, and motivate readers to use phishing prevention. With a large number of phishing emails or messages coming today, it is for businesses or individuals impossible to find them.

Keywords: Phishing website; Phishing URL Detection; Machine learning. (search for similar items in EconPapers)
Date: 2023
Note: Article URL: https://ijsrcseit.com/CSEIT2390227
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v9:y2023:i2:id:hcseit2390227

DOI: 10.32628/CSEIT2390227

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