Open AccessPhishing Website Detection using Machine Learning
Author(s) -
Rajendra Kankrale
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.35671
Subject(s) - phishing , computer science , random forest , personally identifiable information , internet privacy , information sensitivity , focus (optics) , computer security , world wide web , artificial intelligence , the internet , physics , optics
Phishing is not a legal activity, in this people are misguided into the wrong websites using various types of fraudulent methods. The main objective of this phishing websites is to seize all personal information or financial details for own personal benefits or misuse. As the technology facilitates, the phishing approaches used needs to get progressed and therefore there is urgent need for better security and better mechanisms to prevent as well as detect this phishing approaches. The primary focus of this paper to put forward a model as a solution to detect phishing websites by using the URL detection using Random Forest Algorithm. There are basically three major phases such.