TY - JOUR
T1 - Detecting attacks on e-mail
AU - Fang, Yujia
AU - Mogos, Gabriela
N1 - Publisher Copyright:
© 2024 Institute of Advanced Engineering and Science. All rights reserved.
PY - 2024/3
Y1 - 2024/3
N2 - E-mail has become a popular communication tool widely used by universities, enterprises and governments. Despite the convenience it brought to people, attacks on e-mail happen very frequently in the range of the world, causing large economic loss and occupying a mass of network bandwidth every year. The hazards from e-mail attacks underline the importance of detecting and resisting spam in an efficient and timely way. Using Python, we built Naive Bayes (NB) and support vector machine (SVM) filters for emails. The filtering performance of NB and SVM email filters applying different kernel functions was compared and evaluated based on several evaluation indices including accuracy, precision, and total cost ratio (TCR). Also, in order to optimize the filters, the influences of stop words removal, feature numbers and other parameters in the filtering algorithms were monitored.
AB - E-mail has become a popular communication tool widely used by universities, enterprises and governments. Despite the convenience it brought to people, attacks on e-mail happen very frequently in the range of the world, causing large economic loss and occupying a mass of network bandwidth every year. The hazards from e-mail attacks underline the importance of detecting and resisting spam in an efficient and timely way. Using Python, we built Naive Bayes (NB) and support vector machine (SVM) filters for emails. The filtering performance of NB and SVM email filters applying different kernel functions was compared and evaluated based on several evaluation indices including accuracy, precision, and total cost ratio (TCR). Also, in order to optimize the filters, the influences of stop words removal, feature numbers and other parameters in the filtering algorithms were monitored.
KW - Bayesian filter
KW - E-mail filtering
KW - Machine learning
KW - Spam
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=85185806805&partnerID=8YFLogxK
U2 - 10.11591/ijeecs.v33.i3.pp1576-1588
DO - 10.11591/ijeecs.v33.i3.pp1576-1588
M3 - Article
AN - SCOPUS:85185806805
SN - 2502-4752
VL - 33
SP - 1576
EP - 1588
JO - Indonesian Journal of Electrical Engineering and Computer Science
JF - Indonesian Journal of Electrical Engineering and Computer Science
IS - 3
ER -