Application of random forest machine Learning algorithm for spam email Classification · Electronic Theses and Dissertations

Author: Munoshamisa Z. Veruh
Title: Application of random forest machine
Learning algorithm for spam email
Classification
Abstract: Abstract
It is clear from analysing how common phishing email attacks are in today's technological environment that many regular email users become victims because they are unable to make wise decisions. This vulnerability results from phishing emails' sophisticated design, which makes it possible for them to get past typical spam filters. Meanwhile, online communication is being greatly impacted by natural language processing (NLP), which is quickly becoming recognised in a variety of high-tech areas. As such, NLP integration into email phishing categorization systems is crucial. This work explores text processing and categorization, building the classifier with the Random Forest algorithm. Although there are a number of techniques for identifying phishing emails, the use of natural language processing (NLP) in this situation has not received enough attention.
Date: JUNE 2024
Publisher: BUSE
Keywords: phishing email attacks, typical spam filters, natural language processing (NLP).
Supervisor: Mr O Muzurura