An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization.
- DOI
- 10.1038/s41598-026-58514-x
- Published
- 2026-07-09
- Container
- Sci Rep
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- supportingDirectory of Open Access Journals: A matching record was returned by DOAJ.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-58514-x,
title = {An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization.},
author = {Saykat MTH and Haque ME and Farid FA and Hossen R and Uddin J and Karim HBA.},
year = {2026},
journal = {Sci Rep},
doi = {10.1038/s41598-026-58514-x},
url = {https://doi.org/10.1038/s41598-026-58514-x}
}RIS
TY - JOUR TI - An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization. AU - Saykat MTH AU - Haque ME AU - Farid FA AU - Hossen R AU - Uddin J AU - Karim HBA. PY - 2026 JO - Sci Rep DO - 10.1038/s41598-026-58514-x UR - https://doi.org/10.1038/s41598-026-58514-x ER -
APA
MTH, S., ME, H., FA, F., R, H., J, U., & HBA., K. (2026). An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization.. Sci Rep. https://doi.org/10.1038/s41598-026-58514-x
Source records
- europe-pmc · retrieved 2026-09-25T22:28:10.749Z
- doaj · retrieved 2026-09-25T22:28:10.749Z