Evaluating ML-based anomaly detection across datasets of varied integrity: A case study-Reference-Cited by-同舟云学术

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Evaluating ML-based anomaly detection across datasets of varied integrity: A case study

Published:2024-09 Issue: Volume:251 Page:110617
ISSN:1389-1286
Container-title:Computer Networks
language:en
Short-container-title:Computer Networks

Author:

Pekar Adrian^ORCID,Jozsa Richard

Publisher

Elsevier BV

Reference19 articles.

1. Datasets;Canadian Institute for Cybersecurity,2024

2. UNSW-NB15: A comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set);Moustafa,2015

3. LITNET-2020: An annotated real-world network flow dataset for network intrusion detection;Damasevicius;Electronics,2020

4. Generating network intrusion detection dataset based on real and encrypted synthetic attack traffic;Ferriyan;Appl. Sci.,2021

5. NetFlow datasets for machine learning-based network intrusion detection systems;Sarhan,2021

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