The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Data Mining: Practical Machine Learning Tools and Techniques
(2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,437
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
Witten, I. H. (2008) · Cited by 9,143
A detailed analysis of the KDD CUP 99 data set
Tavallaee, M., Bagheri, E., Lu, W., & Ghorbani, A. A. (2009) · 2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications · doi:10.1109/cisda.2009.5356528 · Cited by 5,396
Friedman, N., Geiger, D., & Goldszmidt, M. (1997) · Machine Learning · doi:10.1023/a:1007465528199 · Cited by 4,742
(1998) · Cited by 3,476
Denning, D. E. (1987) · IEEE Transactions on Software Engineering · doi:10.1109/tse.1987.232894 · Cited by 3,427
Selection of relevant features and examples in machine learning
Blum, A. L., & Langley, P. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00063-5 · Cited by 3,298
Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning
Fayyad, U. M., & Irani, K. B. (1993) · International Joint Conference on Artificial Intelligence · Cited by 2,870
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
Cybersecurity data science: an overview from machine learning perspective
Sarker, I. H., Kayes, A. S. M., Badsha, S., Alqahtani, H., Watters, P., & Ng, A. (2020) · Journal of Big Data · doi:10.1186/s40537-020-00318-5 · Cited by 766
IntruDTree: A Machine Learning Based Cyber Security Intrusion Detection Model
Sarker, I. H., Abushark, Y. B., Alsolami, F., & Khan, A. I. (2020) · Symmetry · doi:10.3390/sym12050754 · Cited by 356
Sarker, I. H. (2021) · Internet of Things · doi:10.1016/j.iot.2021.100393 · Cited by 129
M-AdaBoost-A based ensemble system for network intrusion detection
Zhou, Y., Mazzuchi, T. A., & Sarkani, S. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113864 · Cited by 99
Self-citation
Metadata
- Authors
- Koc, L., Mazzuchi, T. A., & Sarkani, S.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2012-12
- Volume
- 39
- Issue
- 18
- Pages
- 13492-13500
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W1983291981
- Cited by
- 310
- References
- 54
- FWCI
- 22.37
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier. https://app.cochat.ai/papers/10.1016/j.eswa.2012.07.009
- The paper
- Koc, L., Mazzuchi, T. A., & Sarkani, S. (2012). A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2012.07.009
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.
