Abstract
Today's world is heading towards complete digital transformation, and with all its advantages, this transformation involves many risks, the most important of which is phishing. This paper proposes a system that classifies the email as phishing or legitimate. Initially, the samples were brought from different data sets, and then the system extracts the features from all parts of the email. The proposed system uses one of the machine learning algorithms (K-means algorithm) to select the valuable features; the proposed system uses four methods to calculate the distance in the K-means algorithm. After features selection, The paper uses ANN as a classifier to classify emails into phishing and ham, and the proposed system tunes the parameters of ANN to obtain a high percentage of accuracy. The proposed system gave an accuracy equal to 99.4%
Recommended Citation
Nabet, Majeed Jasim and George, Loay E.
(2023)
"Phishing Attacks Detection by Using Artificial Neural Networks,"
Iraqi Journal for Computer Science and Mathematics: Vol. 4:
Iss.
3, Article 13.
DOI: https://doi.org/10.52866/ijcsm.2023.02.03.013
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol4/iss3/13
