Intrusion Detection Systems based on Machine Learning

Oumaima Chentoufi, Khalid Chougdali

2021

Abstract

This paper contains an introduction to intrusion detection systems known as IDS. There are two types of techniques to detect an intrusion, misuse detection and anomaly detection; both can be used in a complementary way to increase the system’s efficiency is used for EMERALD, JiNao... It was determined that using machine learning for IDS is an efficient way to detect attacks, and this paper will provide information about machine learning and its classifiers.

Paper Citation

in Harvard Style

Chentoufi O. and Chougdali K. (2021). Intrusion Detection Systems based on Machine Learning. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 355-359. DOI: 10.5220/0010734300003101

in Bibtex Style

@conference{bml21,
author={Oumaima Chentoufi and Khalid Chougdali},
title={Intrusion Detection Systems based on Machine Learning},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={355-359},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010734300003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Intrusion Detection Systems based on Machine Learning
SN - 978-989-758-559-3
AU - Chentoufi O.
AU - Chougdali K.
PY - 2021
SP - 355
EP - 359
DO - 10.5220/0010734300003101