PHISHING WEBSITE DETECTION

SHAIK SHAHINA; D MURALI

PHISHING WEBSITE DETECTION

Authors: SHAIK SHAHINA, D MURALI

Unique Paper ID: 169559
Volume: 11
Issue: 6
PageNo: 1256-1260

Keywords: Phishing Detection API URLs Machine learning models logistic regression.

Abstract:
Online phishing is one of the most common attacks on the modern internet. The goal of phishing website uniform resource locators is to steal personal data including login credentials and credit card numbers. As technology keeps growing, phishing strategies began to develop rapidly. Machine learning built an effective device used to attempt phishing attacks. In this project, we have built a phishing website by using fast API. We have used two so many different libraries and two algorithms which are logistic regression and multimodal NP. The purpose of this project is to check whether phishing websites are good URLs or bad URLs. We gathered data to create a dataset of malicious links and curate it for the machine learning model.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 6
PageNo: 1256-1260

PHISHING WEBSITE DETECTION

Available:https://ijirt.org/Article?manuscript=169559

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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