The DOI matches its Crossref record.
Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system
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 Novel Deep Learning-Based Intrusion Detection System for IoT Networks
Awajan, A. (2023) · Computers · doi:10.3390/computers12020034 · Cited by 292
Brenner, B., Hollerer, S., Bhosale, P., Sauter, T., Kastner, W., Fabini, J., & Zseby, T. (2023) · IEEE Open Journal of the Industrial Electronics Society · doi:10.1109/ojies.2023.3297057 · Cited by 12
Shafi, M., Lashkari, A. H., & Roudsari, A. H. (2025) · Journal of Network and Systems Management · doi:10.1007/s10922-025-09917-0 · Cited by 10
Metadata
- Authors
- Ravi, V., Chaganti, R., & Alazab, M.
- Venue
- Computers and Electrical Engineering
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 102
- Pages
- 108156
- ISSN
- 0045-7906 (ISSN-L)
- OpenAlex
- W4283019189
- Cited by
- 187
- References
- 0
- FWCI
- 18.85
- 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: Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system. https://app.cochat.ai/papers/10.1016/j.compeleceng.2022.108156
- The paper
- Ravi, V., Chaganti, R., & Alazab, M. (2022). Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system. Computers and Electrical Engineering. https://doi.org/10.1016/j.compeleceng.2022.108156
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.
