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...
| Main Authors: | , , , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
2015
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| 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 |
| _version_ | 1848837417157525504 |
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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 |