Detection of Phishing Websites through Computational Intelligence

被引:0
|
作者
Suleman, Muhammad Taseer [1 ]
Ali, Amir [2 ]
机构
[1] Lahore Garrison Univ, Digital Forens Res & Serv Ctr, Lahore, Pakistan
[2] Xi An Jiao Tong Univ, Sch Cyber Sci & Engn, Xian 710049, Shannxi, Peoples R China
关键词
web phishing; hacking; machine learning; classification;
D O I
10.1109/ICIC53490.2021.9693034
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Phishing is a technique used by hackers to fool internet users reveal their sensitive information like passwords, credit card numbers, contact information, and address, etc. Web phishing is carried out mostly by sending fake web links to the users through different communication means like Email, Facebook Messenger and WhatsApp, etc. Web phishing detection is significant for making internet browsing safe and secure for users. Different approaches were applied for the detection of fake websites. However, the most efficient method for detecting phishing websites is the one that is based on artificial intelligence and learning mechanism. In this research, an efficient and accurate method is proposed for the detection of phishing websites which is based on computational intelligence. Through the development of different computational models and rigorous testing, it was revealed that Extreme Gradient Boost (XGBoost) based model achieved the maximum scores in all the validation tests. This shows that the model is robust and accurate in terms of web-phishing detection.
引用
收藏
页码:313 / 319
页数:7
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