The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems
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Cites
The WEKA data mining software: an update
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750
Cited by
Survey of intrusion detection systems: Techniques, datasets and challenges
Khraisat, A., Gondal, I., Vamplew, P., & Kamruzzaman, J. (2019) · Cybersecurity · doi:10.1186/s42400-019-0038-7 · Cited by 2,024
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Zhou, Y., Cheng, G., Jiang, S., & Dai, M. (2020) · Computer Networks · doi:10.1016/j.comnet.2020.107247 · Cited by 675
Khraisat, A., & Alazab, A. (2021) · Cybersecurity · doi:10.1186/s42400-021-00077-7 · Cited by 508
A GA-LR wrapper approach for feature selection in network intrusion detection
Khammassi, C., & Krichen, S. (2017) · Computers & Security · doi:10.1016/j.cose.2017.06.005 · Cited by 382
TSDL: A Two-Stage Deep Learning Model for Efficient Network Intrusion Detection
Khan, F. A., Gumaei, A., Derhab, A., & Hussain, A. (2019) · IEEE Access · doi:10.1109/access.2019.2899721 · Cited by 353
Metadata
- Authors
- Elhag, S., Fernández, A., Bawakid, A., Alshomrani, S., & Herrera, F.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 42
- Issue
- 1
- Pages
- 193-202
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2168573734
- Cited by
- 197
- References
- 1
- FWCI
- 19.65
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems. https://app.cochat.ai/papers/10.1016/j.eswa.2014.08.002
- The paper
- Elhag, S., Fernández, A., Bawakid, A., Alshomrani, S., & Herrera, F. (2015). On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2014.08.002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
