Detecting Spam Vietnamese Email
Tisenko Victor Nikolaevich1, Lai Van Duong2, Ha Tuan Anh3, Nguyen Quang Dam4, Nguyen Quoc Hoang5
1Tisenko Victor Nikolaevich, Peter the Great St. Petersburg Polytechnic University, Russia, St.Petersburg, Polytechnicheskaya,
2Lai Van Duong, FPT University Hanoi, Vietnam Ha Tuan Anh, FPT 3University Hanoi, Vietnam
4Nguyen Quang Dam, FPT University Hanoi, Vietnam.
5Nguyen Quoc Hoang, FPT University Hanoi, Vietnam.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 10, 2020. | PP: 1207-1213| Volume-9 Issue-5, March 2020. | Retrieval Number: F3340049620/2020©BEIESP | DOI: 10.35940/ijitee.F3340.049620
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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: Spam messages have been causing much impact on email users. There are many different techniques and measures applied to detect and classify spam messages with other emails. Filters have been installed and configured to detect spam emails based on their identifying characteristics. However, relying only on filters is very easy to miss spam emails because spammers often try to use techniques to bypass the filter’s control. The most effective approach in spam detection today is to find ways to analyze the content of emails. However, it is recognized that each natural language will have different analytical and identification characteristics, so it is not possible to use the same technique or method for all languages. In this paper, we will present a method to detect Vietnamese email based on the process of analyzing email content in both HTML and image formats. machine learning, spam, spam detection.
Keywords: HTML.
Scope of the Article: Nano Ubiquitous Computing