Phishing email detection technique by using hybrid features

Lew, May Form (2014) Phishing email detection technique by using hybrid features. [Final Year Project Report] (Unpublished)

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Abstract

Email provides convenience of communicating to such large number of people, especially for businessman. However, more attacks are launched to target electronic communication user in order to harvest credentials information from them for illegal purpose used. The most commonly phishing method is initialed by sending out email to user tends to make the user believe that they are communicating with trusted enttify, and deceive them into providing personal information. Recently, there are a lot of research have been done to overcome the phishing emails problem. This project aim to design a phishing email detection technique and focus on feature selection. The proposed method contains content-based feature. URL-based feature and behavior-based feature, which total nine feature sets. The proposed method has been evaluated on a set of 500 phishing emails and 500 legitimate emails. The proposed method obtain overall occuracy 97.25% with 1% false negative rate and 5% false positive rate. The proposed method able to classify more occurotely than the hybrid feature proposed by Hamid et al.. This evidence that two newly add on feature sets, hyperlink feature and return path feature are potential indicator. The quite promising result is motivated future work to mine the attacker behavior and explore more about behavior-based feature.

Item Type: Final Year Project Report
Additional Information: Project Report (B.Sc.) -- Universiti Malaysia Sarawak, 2014.
Uncontrolled Keywords: electronic communication, proposed method, feature sets
Subjects: L Education > L Education (General)
Q Science > QA Mathematics
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Dan
Date Deposited: 04 Aug 2022 04:36
Last Modified: 04 Aug 2022 04:36
URI: http://ir.unimas.my/id/eprint/39079

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