TAE-IDS: a trust-aware explainable intrusion detection framework using attention-based meta-ensemble learning with blockchain validation.

Raj SAJ, Madiajagan M

DOI: 10.3389/frai.2026.1903112
Published: 2026
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1903112,
  title = {TAE-IDS: a trust-aware explainable intrusion detection framework using attention-based meta-ensemble learning with blockchain validation.},
  author = {Raj SAJ and Madiajagan M},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1903112},
  url = {https://doi.org/10.3389/frai.2026.1903112}
}

RIS

TY  - JOUR
TI  - TAE-IDS: a trust-aware explainable intrusion detection framework using attention-based meta-ensemble learning with blockchain validation.
AU  - Raj SAJ
AU  - Madiajagan M
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1903112
UR  - https://doi.org/10.3389/frai.2026.1903112
ER  -

APA

SAJ, R., & M, M. (2026). TAE-IDS: a trust-aware explainable intrusion detection framework using attention-based meta-ensemble learning with blockchain validation.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1903112

Source records

pubmed · retrieved 2026-09-25T11:47:48.734Z