
Review on Phishing Attack Detection using Recurrent Neural Network
Author(s) -
Vaibhav Handge,
Shubham Pokale,
Saurabh Lavhate,
Shubham Nalkol,
Prof G. B. Kote
Publication year - 2022
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-3341
Subject(s) - phishing , computer science , web crawler , computer security , world wide web , the internet
Phishing is a crime that involves the theft of personal information from users. Individuals, corporations, cloud storage, and government websites are all targets for the phishing websites. Anti-phishing technologies based on hardware are commonly utilised, while software-based options are preferred due to cost and operational considerations. Current phishing detection systems have no solution for problems like zero-day phishing assaults. To address these issues, a three-phase attack detection system called the Phishing Attack Detector based on Web Crawler was suggested, which uses a recurrent neural network to precisely detect phishing incidents. Based on the classification of phishing and non-phishing pages, it covers the input features Web traffic, web content, and Uniform Resource Locator (URL).