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A Framework for Multi Features based Phishing Information Identification using NB and SVM Approach

by Jyoti S. Kharat, Snehal S. Shinde, Anjali P. Deore
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 27
Year of Publication: 2018
Authors: Jyoti S. Kharat, Snehal S. Shinde, Anjali P. Deore
10.5120/ijca2018918088

Jyoti S. Kharat, Snehal S. Shinde, Anjali P. Deore . A Framework for Multi Features based Phishing Information Identification using NB and SVM Approach. International Journal of Computer Applications. 181, 27 ( Nov 2018), 31-36. DOI=10.5120/ijca2018918088

@article{ 10.5120/ijca2018918088,
author = { Jyoti S. Kharat, Snehal S. Shinde, Anjali P. Deore },
title = { A Framework for Multi Features based Phishing Information Identification using NB and SVM Approach },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2018 },
volume = { 181 },
number = { 27 },
month = { Nov },
year = { 2018 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number27/30110-2018918088/ },
doi = { 10.5120/ijca2018918088 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:09:55.824109+05:30
%A Jyoti S. Kharat
%A Snehal S. Shinde
%A Anjali P. Deore
%T A Framework for Multi Features based Phishing Information Identification using NB and SVM Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 27
%P 31-36
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Criminal organizations around the world use the technique known as phishing to extract information from innocent citizens in order to access their bank details, to steal identities, to launder money and more. There are Different types of statistical learning based classification methods are available to differentiate the phishing webpage’s from the original. Feature extraction method is the concept, which has been implementing into the development of web phishing information detection technique. Naïve Bayes and SVM statistical algorithms are used for feature extraction of URL and source code respectively. In contrast to other proposals, this scheme has a high detection rate and a low false negative rate as well as can achieve high detection accuracy, the lower detection time and performance with the small sample of a classification model training set.

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Index Terms

Computer Science
Information Sciences

Keywords

SVM Phisher Naïve Bayes Multi features

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