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Detection and Binary Classification of Spear-Phishing Emails in Organizations Using a Hybrid Machine Learning Approach by Popoola Favourite Akinwale; Hamid Jahankhani is a book available to read on EtoBox.

What is Detection and Binary Classification of Spear-Phishing Emails in Organizations Using a Hybrid Machine Learning Approach about?

In recent years, e-mails have become the most commonly used information and communication technology in organization. The email technology is susceptible to phishing attacks. Phishing attacks are a trending cybercrime activity and have caused a lot of financial loss using social engineered communication that are transmitted to individuals by cybercriminals aimed at tricking users to share sensitive information, with emails being the prevalent attack vector. Spear-phishing is a deceptive social engineering tool used to capture targeted victim's personal data or information. Social engineering is a cyber threat that aims to use psychological techniques to manipulate or trick people to expose their personal/sensitive information. In this research paper, five supervised classification algorithms (Logistic Regression, Random Forest, Decision Tree, Support Vector Machine and K-Nearest Neighbour) are discussed and compared. A pre-processing system has been designed to collect and extract the features and patterns of spear-phishing emails from the email header and email body. In addition, using the top two classifiers, Logistic Regression and Decision Tree, a novel technique for detecting

Author

Popoola Favourite Akinwale; Hamid Jahankhani

Publisher

Springer International Publishing : Imprint: Springer

Published

2021

Language

EN

ISBN

9783030880415

Subjects

Science, Philosophy, Computer Science