The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
A novel SVM-kNN-PSO ensemble method for intrusion detection system
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Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
A modified particle swarm optimizer
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The Weighted Majority Algorithm
Littlestone, N., & Warmuth, M. K. (1994) · Information and Computation · doi:10.1006/inco.1994.1009 · Cited by 1,975
2011 IEEE Congress of Evolutionary Computation (CEC)
(2011) · doi:10.1109/cec15497.2011 · Cited by 487
Proceedings of IEEE International Conference on Evolutionary Computation
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A novel intrusion detection system based on hierarchical clustering and support vector machines
Horng, S.-J., Su, M.-Y., Chen, Y.-H., Kao, T.-W., Chen, R.-J., Lai, J.-L., & Perkasa, C. D. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.06.066 · Cited by 460
Modeling intrusion detection system using hybrid intelligent systems
Peddabachigari, S., Abraham, A., Grosan, C., & Thomas, J. (2007) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2005.06.003 · Cited by 434
A novel hybrid KPCA and SVM with GA model for intrusion detection
Kuang, F., Xu, W., & Zhang, S. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.01.028 · Cited by 424
Particle Swarm Optimization and Intelligence: Advances and Applications
Parsopoulos, K. E., & Vrahatis, M. N. (2010) · doi:10.13140/2.1.3681.1206 · Cited by 371
Lin, S.-W., Ying, K.-C., Lee, C.-Y., & Lee, Z.-J. (2012) · Applied Soft Computing · doi:10.1016/j.asoc.2012.05.004 · Cited by 226
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
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988293 · Cited by 1,392
A comprehensive review on ensemble deep learning: Opportunities and challenges
Mohammed, A., & Kora, R. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.01.014 · Cited by 1,127
Ensemble of keyword extraction methods and classifiers in text classification
Onan, A., Korukoğlu, S., & Bulut, H. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.03.045 · Cited by 630
Khraisat, A., & Alazab, A. (2021) · Cybersecurity · doi:10.1186/s42400-021-00077-7 · Cited by 508
Metadata
- Authors
- Aburomman, A. A., & Ibne Reaz, M. B.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 38
- Pages
- 360-372
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2191006491
- Cited by
- 490
- References
- 18
- FWCI
- 39.91
- Type
- journal article
- Language
- en
- Open access
- closed
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- Aburomman, A. A., & Ibne Reaz, M. B. (2016). A novel SVM-kNN-PSO ensemble method for intrusion detection system. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2015.10.011
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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.
