Analyzing and contrasting machine learning algorithms for Intrusion Detection System-Reference-Cited by-同舟云学术

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Analyzing and contrasting machine learning algorithms for Intrusion Detection System

Published:2023-12-06 Issue: Volume:5 Page:1-6
ISSN:
Container-title:2023 24th International Arab Conference on Information Technology (ACIT)
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Author:

Al-Daja Shrouq¹,Ala'Alyabrodi ²,Al-Mousa Mohammad Rasmi²,Al-Qammaz Abdullah²,Olimat Kholod Naser³,Olemat Hamza M⁴,Daoud Mohammad Sh⁵

Affiliation:

1. Zarqa University,Department of Data Science and Artificial Intelligence,Zarqa,Jordan

2. Zarqa University,Department of Cyber Security,Zarqa,Jordan

3. Zarqa University,Department of English and Literature,Zarqa,Jordan

4. Zarqa University,Department of Computer Science,Zarqa,Jordan

5. College of Engineering, Al Ain University,Abu Dhabi,United Arab Emirates

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10453649/10453660/10453827.pdf?arnumber=10453827

Reference26 articles.

1. Intrusion detection system: A comprehensive review

2. Survey of intrusion detection systems: techniques, datasets and challenges

3. Evaluation of Machine Learning Algorithms for Anomaly Detection

4. Benchmarking of Machine Learning for Anomaly Based Intrusion Detection Systems in the CICIDS2017 Dataset

5. Characterization of Tor Traffic using Time based Features

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