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Reseach Article

Efficient Detection of Legitimate and Malicious URLs using ID3 Algorithm

by Yogesh Dubey, Pranil Chaudhari, Shaldon Chaphya, Tina D�abreo
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 11
Year of Publication: 2017
Authors: Yogesh Dubey, Pranil Chaudhari, Shaldon Chaphya, Tina D�abreo
10.5120/ijais2017451660

Yogesh Dubey, Pranil Chaudhari, Shaldon Chaphya, Tina D�abreo . Efficient Detection of Legitimate and Malicious URLs using ID3 Algorithm. International Journal of Applied Information Systems. 11, 11 ( Mar 2017), 53-55. DOI=10.5120/ijais2017451660

@article{ 10.5120/ijais2017451660,
author = { Yogesh Dubey, Pranil Chaudhari, Shaldon Chaphya, Tina D�abreo },
title = { Efficient Detection of Legitimate and Malicious URLs using ID3 Algorithm },
journal = { International Journal of Applied Information Systems },
issue_date = { Mar 2017 },
volume = { 11 },
number = { 11 },
month = { Mar },
year = { 2017 },
issn = { 2249-0868 },
pages = { 53-55 },
numpages = {9},
url = { https://www.ijais.org/archives/volume11/number11/973-2017451660/ },
doi = { 10.5120/ijais2017451660 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:04:57.118837+05:30
%A Yogesh Dubey
%A Pranil Chaudhari
%A Shaldon Chaphya
%A Tina D�abreo
%T Efficient Detection of Legitimate and Malicious URLs using ID3 Algorithm
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 11
%N 11
%P 53-55
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Malicious websites are one of the serious threat over the internet. Ever since the inception of the internet, there has been a rise in malicious content over the web such has terrorism, financial fraud, phishing and hacking that targets user’s personal information. Till date, the various systems have been used for the detection of a malicious website based on text and content of the websites. This method has some disadvantages and the numbers of victims have therefore continued to increase. Here we developed a system which helps the user to identify whether the website is malicious or not. Our system identifies whether the site is malicious or not through URL. The proposed system is fast and more accurate compared to current system. The classifier is trained with datasets of 1000 malicious sites and 1000 legitimate site URLs. Trained classifier is used for detection of malicious URLs.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Malicious URLs Classifier Feature Extraction ID3 Algorithm