Phishing Email Detection Technique by using Hybrid Features

Phishing emails is growing at an alarming rate in this few years. It has caused tremendous financial losses to internet users. Phishing techniques getting more advance everyday and this has created great challenge to the existing anti-phishing techniques. Hence, in this paper, we proposed to de...

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Main Authors: Lew, May Form, Kang, Leng Chiew, San, Nah Sze, Wei, King Tiong
Format: Proceeding
Language:English
Published: 2015
Subjects:
Online Access:http://ir.unimas.my/id/eprint/13468/
http://ir.unimas.my/id/eprint/13468/1/Phishing%20Email%20Detection%20Technique%20by%20using%20Hybrid%20Features%20%28abstract%29.pdf
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author Lew, May Form
Kang, Leng Chiew
San, Nah Sze
Wei, King Tiong
author_facet Lew, May Form
Kang, Leng Chiew
San, Nah Sze
Wei, King Tiong
author_sort Lew, May Form
building UNIMAS Institutional Repository
collection Online Access
description Phishing emails is growing at an alarming rate in this few years. It has caused tremendous financial losses to internet users. Phishing techniques getting more advance everyday and this has created great challenge to the existing anti-phishing techniques. Hence, in this paper, we proposed to detect phishing emails through hybrids features. The hybrid features consist of content-based, URL-based, and behaviorbased features. Based on a set of 500 phishing emails and 500 legitimate emails, the proposed method achieved overall accuracy of 97.25% and error rate of 2.75%. This promising result verify the effectiveness of the proposed hybrid features in detecting phishing email.
first_indexed 2025-11-15T06:39:19Z
format Proceeding
id unimas-13468
institution Universiti Malaysia Sarawak
institution_category Local University
language English
last_indexed 2025-11-15T06:39:19Z
publishDate 2015
recordtype eprints
repository_type Digital Repository
spelling unimas-134682017-02-14T06:25:32Z http://ir.unimas.my/id/eprint/13468/ Phishing Email Detection Technique by using Hybrid Features Lew, May Form Kang, Leng Chiew San, Nah Sze Wei, King Tiong T Technology (General) Phishing emails is growing at an alarming rate in this few years. It has caused tremendous financial losses to internet users. Phishing techniques getting more advance everyday and this has created great challenge to the existing anti-phishing techniques. Hence, in this paper, we proposed to detect phishing emails through hybrids features. The hybrid features consist of content-based, URL-based, and behaviorbased features. Based on a set of 500 phishing emails and 500 legitimate emails, the proposed method achieved overall accuracy of 97.25% and error rate of 2.75%. This promising result verify the effectiveness of the proposed hybrid features in detecting phishing email. 2015 Proceeding NonPeerReviewed text en http://ir.unimas.my/id/eprint/13468/1/Phishing%20Email%20Detection%20Technique%20by%20using%20Hybrid%20Features%20%28abstract%29.pdf Lew, May Form and Kang, Leng Chiew and San, Nah Sze and Wei, King Tiong (2015) Phishing Email Detection Technique by using Hybrid Features. In: 2015 9th International Conference on IT in Asia (CITA) : Transforming Big Data into Knowledge, 4-5 August 2015, Kuching, Sarawak Malaysia.
spellingShingle T Technology (General)
Lew, May Form
Kang, Leng Chiew
San, Nah Sze
Wei, King Tiong
Phishing Email Detection Technique by using Hybrid Features
title Phishing Email Detection Technique by using Hybrid Features
title_full Phishing Email Detection Technique by using Hybrid Features
title_fullStr Phishing Email Detection Technique by using Hybrid Features
title_full_unstemmed Phishing Email Detection Technique by using Hybrid Features
title_short Phishing Email Detection Technique by using Hybrid Features
title_sort phishing email detection technique by using hybrid features
topic T Technology (General)
url http://ir.unimas.my/id/eprint/13468/
http://ir.unimas.my/id/eprint/13468/1/Phishing%20Email%20Detection%20Technique%20by%20using%20Hybrid%20Features%20%28abstract%29.pdf