The DOI matches its Crossref record.
Mutual information-based feature selection for intrusion detection systems
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
Cited by
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Buczak, A. L., & Guven, E. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2494502 · Cited by 3,332
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
From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Nisioti, A., Mylonas, A., Yoo, P. D., & Katos, V. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2854724 · Cited by 212
Sarker, I. H. (2021) · Internet of Things · doi:10.1016/j.iot.2021.100393 · Cited by 129
FSCB-IDS: Feature Selection and Minority Class Balancing for Attacks Detection in VANETs
Amaouche, S., Guezzaz, A., Benkirane, S., Azrour, M., Khattak, S. B. A., Farman, H., & Nasralla, M. M. (2023) · Applied Sciences · doi:10.3390/app13137488 · Cited by 42
Metadata
- Authors
- Amiri, F., Rezaei Yousefi, M., Lucas, C., Shakery, A., & Yazdani, N.
- Venue
- Journal of Network and Computer Applications
- Publisher
- Elsevier BV
- Published
- 2011-07
- Volume
- 34
- Issue
- 4
- Pages
- 1184-1199
- ISSN
- 1084-8045 (ISSN-L)
- OpenAlex
- W2076384720
- Cited by
- 471
- References
- 0
- FWCI
- 29.11
- 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: Mutual information-based feature selection for intrusion detection systems. https://app.cochat.ai/papers/10.1016/j.jnca.2011.01.002
- The paper
- Amiri, F., Rezaei Yousefi, M., Lucas, C., Shakery, A., & Yazdani, N. (2011). Mutual information-based feature selection for intrusion detection systems. Journal of Network and Computer Applications. https://doi.org/10.1016/j.jnca.2011.01.002
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.