Open AccessPhishing website detection using machine learning and deep learning techniques
Author(s) -
M Selvakumari,
M Sowjanya,
Sneha Das,
S Padmavathi
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1916/1/012169
Subject(s) - phishing , spoofing attack , computer science , identity theft , credit card , the internet , computer security , world wide web , internet privacy , internet users , malware , artificial intelligence , payment
Phishing has become more damaging nowadays because of the rapid growth of internet users. The phishing attack is now a big threat to people’s daily life and to the internet environment. In these attacks, the attacker impersonates a trusted entity intending to steal sensitive information or the digital identity of the user, e.g., account credentials, credit card numbers and other user details. A phishing website is a website which is similar in name and appearance to an official website otherwise known as a spoofed website which is created to fool an individual and steal their personal credentials. So, to identify the websites which are fraud, this paper will discuss the machine learning and deep learning algorithms and apply all these algorithms on our dataset and the best algorithm having the best precision and accuracy is selected for the phishing website detection. This work can provide more effective defenses for phishing attacks of the future.