Data Curation and Quality Evaluation for Machine Learning-Based Cyber Intrusion Detection
Author:
Affiliation:
1. Department of Information Science, Denton, TX, USA
2. Department of Computer Science, Tuskegee University, Tuskegee, AL, USA
Funder
National Science Foundation
National Security Agency
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
https://ieeexplore.ieee.org/ielam/6287639/9668973/9907008-aam.pdf
Reference86 articles.
1. Effect of Class Imbalance on the Performance of Machine Learning-based Network Intrusion Detection
2. SoK: The Impact of Unlabelled Data in Cyberthreat Detection
3. Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternatives
4. Statistical machine learning for network intrusion detection: a data quality perspective
5. Data quality: A statistical perspective
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