A deep learning-based intrusion detection approach for mobile Ad-hoc network
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- Authors
- Meddeb, R., Jemili, F., Triki, B., & Korbaa, O.
- Affiliations
- Institut Supérieur d'Informatique et des Technologies de Communication de Hammam Sousse (TN)
- Corresponding author
- Jemili, Farah
- Venue
- Soft Computing
- Published
- 2023-05-21
- Volume
- 27
- Issue
- 14
- Pages
- 9425-9439
- ISSN
- 1432-7643 (ISSN-L)
- 1433-7479
- OpenAlex
- W4377194846
- Cited by
- 63
- References
- 44
- Citations by year
- 2026: 13 · 2025: 15 · 2024: 25 · 2023: 10
- FWCI
- 7.01
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Soft Computing (publishedVersion)
- Research Square (acceptedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Computer Networks and Communications › Mobile Ad Hoc Networks
- Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
- Keywords
- intrusion detection, mobile ad hoc networks, stacked autoencoder, denial-of-service attacks, routing attacks, network security, feature extraction, deep neural network classifier, correlation reduction
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 ›
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