Beta
199910

Hybrid Client Side Phishing Websites Detection Approach

Article

Last updated: 23 Jan 2023

Subjects

-

Tags

-

Abstract

Phishing tricks to steal personal or credential information by entering victims into a forged website similar to the original site, and urging them to enter their information believing that this site is legitimate. The number of internet users who are becoming victims of phishing attacks is increasing beside that phishing attacks have become more sophisticated. In this paper we propose a client-side solution to protect against phishing attacks which is a Firefox extension integrated as a toolbar that is responsible for checking whether recipient website is trusted or not by inspecting URLs of each requested webpage. If the site is suspicious the toolbar is going to block it. Every URL is evaluated corresponding to features extracted from it. Three heuristics (primary domain, sub domain, and path) and Naïve Bayes classification using four lexical features combined with page ranking received from two different services (Alexa, and Google page rank) used to classify URL. The proposed method requires no server changes and will prevent internet users from fraudulent sites especially from phishing attacks based on deceptive URLs. Experimental results show that our approach can achieve 48% accuracy ratio using a test set of 246 URL, and 87.5% accuracy ratio by excluding NB addition tested over 162 URL.

DOI

10.21608/aeta.2015.199910

Keywords

Phishing Attacks, Browser Plug in, Anti Phishing, security, Firefox

Authors

First Name

Firdous

Last Name

Kausar

MiddleName

-

Affiliation

Department of Computer Science, College of Computer and Information Sciences, Al Imam Muhammad bin Saud Islamic University, Riyadh, Saudi Arabia

Email

-

City

-

Orcid

-

First Name

Bushra

Last Name

Al-Otaibi

MiddleName

-

Affiliation

Department of Computer Science, College of Computer and Information Sciences, Al Imam Muhammad bin Saud Islamic University, Riyadh, Saudi Arabia

Email

-

City

-

Orcid

-

First Name

Asma

Last Name

Al-Qadi

MiddleName

-

Affiliation

Department of Computer Science, College of Computer and Information Sciences, Al Imam Muhammad bin Saud Islamic University, Riyadh, Saudi Arabia

Email

-

City

-

Orcid

-

First Name

Nwayer

Last Name

Al-Dossari.

MiddleName

-

Affiliation

Department of Computer Science, College of Computer and Information Sciences, Al Imam Muhammad bin Saud Islamic University, Riyadh, Saudi Arabia

Email

-

City

-

Orcid

-

Volume

4

Article Issue

2

Related Issue

28196

Issue Date

2015-09-01

Receive Date

2021-10-17

Publish Date

2015-09-01

Page Start

1

Page End

9

Print ISSN

2090-9535

Online ISSN

2090-9543

Link

https://aeta.journals.ekb.eg/article_199910.html

Detail API

https://aeta.journals.ekb.eg/service?article_code=199910

Order

199,910

Publication Type

Journal

Publication Title

Advanced Engineering Technology and Application

Publication Link

https://aeta.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

23 Jan 2023