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Vol. 4 No. 01 (2023)

Articles

Web Phishing Detection Using Web Crawling, Cloud Infrastructure and Deep Learning Framework

https://doi.org/10.38094/jastt401144

Published 2023-03-11

  • Lozan Mohammed Abdulrahman
    • ,
  • Sarkar Hasan Ahmed
    • ,
  • Zryan Najat Rashid
    • ,
  • Yousif Sufyan Jghef
    • ,
  • Teba Mohammed Ghazi
    • ,
  • Umed H. Jader

Lozan Mohammed Abdulrahman
ITM Dept., Technical College of Administration, Duhok Polytechnic University, Duhok, Iraq

Sarkar Hasan Ahmed
Computer Networks Dept., Sulaimani Polytechnic University, Sulaimani

Zryan Najat Rashid
Computer Network Dept., Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani

Yousif Sufyan Jghef
Computer Engineering Dept., College of Engineering, Knowledge University, Erbil, Iraq

Teba Mohammed Ghazi
Computer Science Dept., Faculty of Science, University of Zakho, Duhok, Iraq

Umed H. Jader
Information Technology Dept., Erbil Polytechnic University, Erbil, Iraq

Abstract

The pandemic of COVID-19 obliges citizens to follow the “work from home “scheme. The Internet is also a powerful channel for social connections. The huge dependency of people on digital media opens doors to fraud. Phishing is a form of cybercrime that is used to rob users of passwords from online banking, e-commerce, online schools, digital markets, and others. Phishers create bogus websites like the original and deliver users spam mails. When an online user visits fake web pages via spam, phishers steal their credentials. As a result, it is important to identify these forms of fraudulent websites until they do any harm to victims. Inspired by the ever-changing existence of phishing websites. This paper reviews the work on Phishing attack detection and aims to examine techniques that mainly detect and help in preventing phishing attacks rather than mitigating them. Here we offered a general overview of the most effective phishing attack detection strategies focused on deep learning.

Keywords

Phishing, Phishing Website, Phishing Attacks, Phishing Detection, Deep Learning

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