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AN ENHANCEMENT ON TARGETED PHISHING ATTACKS IN THE STATE OF QATAR

Al-Hamar, Y (2019) AN ENHANCEMENT ON TARGETED PHISHING ATTACKS IN THE STATE OF QATAR. Doctoral thesis, Liverpool John Moores University.

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Abstract

The latest report by Kaspersky on Spam and Phishing, listed Qatar as one of the top 10 countries by percentage of email phishing and targeted phishing attacks. Since the Qatari economy has grown exponentially and become increasingly global in nature, email phishing and targeted phishing attacks have the capacity to be devastating to the Qatari economy, yet there are no adequate measures put in place such as awareness training programmes to minimise these threats to the state of Qatar. Therefore, this research aims to explore targeted attacks in specific organisations in the state of Qatar by presenting a new technique to prevent targeted attacks. This novel enterprise-wide email phishing detection system has been used by organisations and individuals not only in the state of Qatar but also in organisations in the UK. This detection system is based on domain names by which attackers carefully register domain names which victims trust. The results show that this detection system has proven its ability to reduce email phishing attacks. Moreover, it aims to develop email phishing awareness training techniques specifically designed for the state of Qatar to complement the presented technique in order to increase email phishing awareness, focused on targeted attacks and the content, and reduce the impact of phishing email attacks. This research was carried out by developing an interactive email phishing awareness training website that has been tested by organisations in the state of Qatar. The results of this training programme proved to get effective results by training users on how to spot email phishing and targeted attacks.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: phishing attacks; smishing; spearphishing attacks; social engineering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Date Deposited: 05 Dec 2019 10:07
Last Modified: 23 Nov 2022 10:05
DOI or ID number: 10.24377/LJMU.t.00011837
Supervisors: Kolivand, H
URI: https://researchonline.ljmu.ac.uk/id/eprint/11837
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