Machine Learning Approach Based Phishing Email Text Analysis (ML-PE-TA)

Phishing based incidents are the procedure of posting illegal or dishonest communications that seems to be originated from a trustworthy sending node. It is commonly reflected in the case of email transmission. The aim is to rob one’s important personal information which includes credit/ debit card details, login information, account related data etc. In one way or another, Phishing emails are can trick users into revealing crucial technical or personal information. Users needs to be very careful and cautious when working with the emails they receive in their Inbox. In addition to verifying sender information, users must be wise enough in analyzing the body of the email to remain protected against such frauds. To account for this reason, this study have proposed a simple yet effective approach, ML-PE-TA,for analyzing the email text body with Machine learning algorithms. Using the proposed approach, this paper could achieve an accuracy of 96 percentage with a minimum count of vital features only for Phishing Email Text Analysis. At the same time, by the application of dimensionality reduction techniques, the proposed approach is able to reduce the dimensionality of the data considerably, which is better than state-of-the-art existing phishing email detection techniques which have much greater number of features and lesser accuracy rate.