Document Type
Article
Publication Date
11-2022
Source Publication
Expert Systems with Applications
Recommended Citation
Chalé, M., & Bastian, N. D. (2022). Generating realistic cyber data for training and evaluating machine learning classifiers for network intrusion detection systems. Expert Systems with Applications, 207, 117936. https://doi.org/10.1016/j.eswa.2022.117936
Comments
AFIT Scholar furnishes the submitted manuscript of the article (preprint), in accordance with sharing policies found at Sherpa.
© 2022 published by Elsevier. This manuscript is made available under the Elsevier user license.
The version of record for the article is accessible by subscription, and appears in volume 207 of Expert Systems with Applications, as fully cited below.
Author M. Chalé was co-affiliated with AFIT at the time of publication.
Funding notes: This work was supported in part by the National Security Agency Laboratory for Advanced Cybersecurity Research under Interagency Agreement No. USMA21035, the U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory under Support Agreement No. USMA21050, and a GEN Omar N. Bradley Foundation Officer Research Fellowship in Mathematics.