Deep Learning, Federated Learning, and Meta-Learning for Intrusion Detection in the Internet of Things: A Systematic Review, Taxonomy, and Research Agenda
- DOI
- 10.21203/rs.3.rs-10756458/v1
- Published
- 2026-09-08
- Container
- Not recorded
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.21203/rs.3.rs-10756458/v1,
title = {Deep Learning, Federated Learning, and Meta-Learning for Intrusion Detection in the Internet of Things: A Systematic Review, Taxonomy, and Research Agenda},
author = {Wilvens PIERRE LOUIS and Mehdi Mehdi Adda},
year = {2026},
doi = {10.21203/rs.3.rs-10756458/v1},
url = {https://doi.org/10.21203/rs.3.rs-10756458/v1}
}RIS
TY - JOUR TI - Deep Learning, Federated Learning, and Meta-Learning for Intrusion Detection in the Internet of Things: A Systematic Review, Taxonomy, and Research Agenda AU - Wilvens PIERRE LOUIS AU - Mehdi Mehdi Adda PY - 2026 DO - 10.21203/rs.3.rs-10756458/v1 UR - https://doi.org/10.21203/rs.3.rs-10756458/v1 ER -
APA
LOUIS, W. P., & Adda, M. M. (2026). Deep Learning, Federated Learning, and Meta-Learning for Intrusion Detection in the Internet of Things: A Systematic Review, Taxonomy, and Research Agenda. https://doi.org/10.21203/rs.3.rs-10756458/v1
Source records
- crossref · retrieved 2026-09-25T19:41:30.868Z