Hybrid Machine Learning Algorithms for Email and Malware Spam Filtering: A Review

Abstract

In this paper, we presented a review of the state-of-the-art hybrid machine learning algorithms that were being used for email effective computing. For this reason, three research questions were formed, and the questions were answered by studying and analyzing related papers collected from some well-established scientific databases (Springer Link, IEEE Explore, Web of Science, and Scopus) based on some exclusion and inclusion criteria. The result presented the common Hybrid ML algorithms used to enhance email spam filtering. Also, the state-of-the-art datasets used for email and malware spam filtering were presented.