A Framework for Vietnamese Email Phishing Detection
Cho Do Xuan1, Hoa Dinh Nguyen2, Tisenko Victor Nikolaevich3

1Cho Do Xuan, Posts and Telecommunications Institute of Technology Hanoi, Vietnam, FPT University Hanoi, Vietnam
2Hoa Dinh Nguyen, Posts and Telecommunications Institute of Technology Hanoi, Vietnam
3Tisenko Victor Nikolaevich, Peter the Great St. Petersburg Polytechnic University Russia, St. Petersburg, Polytechnicheskaya,

Manuscript received on October 13, 2019. | Revised Manuscript received on 25 October, 2019. | Manuscript published on November 10, 2019. | PP: 2258-2264 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4843119119/2019©BEIESP | DOI: 10.35940/ijitee.A4843.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Currently, the attacks on network information systems are increasing rapidly in number and level of danger. Phishing email distribution method is widely used by hackers today. This is an attacking technique that exploits human behaviors in the system. This type of attack, though it is not too complicated, becomes very effective for attackers if users are unaware of information security and unable to identify phishing emails. This attack is particularly more commonly effective in developing countries where the information security is still overlooked. As a result, email phishing detection problem has become a hot topic for information security researchers. There have been some published methods to detect phishing emails on given email attacking datasets. However, one of the important issues in email phishing detection relates to the language used in emails. Each particular language used in different emails may lead to a different phising detection approach. In this article, a Vietnamese email phishing detection system is investigated. The research includes a feature selection method and a combination of machine learning algorithms to improve the performance of phishing email detection in Vietnamese language. The proposed method is evaluated using two datasets. The first dataset includes phishing emails from Vietnamese collected from Vietnamese volunteers. The second dataset is the widely used English emails as introduced in [16,17]. The experimental results show that our method is applicable for real Vietnamese email phishing detection systems.
Keywords: Phishing Detection, Vietnamese Language, Feature Selection, Machine Learning
Scope of the Article: Machine Learning