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Malicious Web Page Detection and Content Analysis

by Vishal Jagtap, Vaibhav Shinde, Pratik Sapre, Kartik Karande, Ketaki Bhoyar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 31
Year of Publication: 2021
Authors: Vishal Jagtap, Vaibhav Shinde, Pratik Sapre, Kartik Karande, Ketaki Bhoyar
10.5120/ijca2021921249

Vishal Jagtap, Vaibhav Shinde, Pratik Sapre, Kartik Karande, Ketaki Bhoyar . Malicious Web Page Detection and Content Analysis. International Journal of Computer Applications. 174, 31 ( Apr 2021), 10-13. DOI=10.5120/ijca2021921249

@article{ 10.5120/ijca2021921249,
author = { Vishal Jagtap, Vaibhav Shinde, Pratik Sapre, Kartik Karande, Ketaki Bhoyar },
title = { Malicious Web Page Detection and Content Analysis },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2021 },
volume = { 174 },
number = { 31 },
month = { Apr },
year = { 2021 },
issn = { 0975-8887 },
pages = { 10-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number31/31876-2021921249/ },
doi = { 10.5120/ijca2021921249 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:23:35.437268+05:30
%A Vishal Jagtap
%A Vaibhav Shinde
%A Pratik Sapre
%A Kartik Karande
%A Ketaki Bhoyar
%T Malicious Web Page Detection and Content Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 31
%P 10-13
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The detection of malicious web pages is a complex engineering problem due to the ​dynamic nature of the information ​contained on the internet.Since the data stored on web-servers updates on a continuous basis, It is very hard to find and classify which links are malicious and which are not in ​real-time. Hence, brute-force checks (system-scans) and voting-based approaches (blacklisting) fail to capture the exhaustive list of malicious content on the internet. A machine learning based model is proposed which is able to classify the malicious links and content on the user’s device. It can later be applied in the forms: a web application, Android, iOS mobile applications and also browser extension which is able to give you a report of that link which you want to open on a device. The whole system performs a complete scan on that link and generates a report.

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Index Terms

Computer Science
Information Sciences

Keywords

Malicious Web Page

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