Peer-reviewedCC BYFrontiers in artificial intelligence
Intelligent defense at the edge: a comprehensive survey of federated learning, TinyML and explainable AI for intrusion detection in IoT and IIoT ecosystems
- 1School of Computer Science and Engineering, Vellore Institute of Technology , ,
Related
- Fed-SecureCvT: optimized federated learning with cryptographic protection and transformer-based intrusion detection for HER
- A resource-aware framework for energy and bandwidth efficient IoT intrusion detection using lightweight federated learning over SDN
- Attentive temporal patch filtering for explainable streaming intrusion detection in medical IoT traffic
- Hybrid post-quantum explainable AI intrusion detection with SDN for heterogeneous IoT networks
- An adaptive federated few-shot learning method with intelligent device selection
BibTeX
@article{kumar2026intelligent,
title = {{Intelligent defense at the edge: a comprehensive survey of federated learning, TinyML and explainable AI for intrusion detection in IoT and IIoT ecosystems}},
author = {S. Sarath Kumar and M. Asha Jerlin},
journal = {Frontiers in artificial intelligence},
year = {2026},
month = oct,
url = {https://europepmc.org/article/PMC/PMC13673141},
note = {CC BY},
}
RIS
TY - JOUR
TI - Intelligent defense at the edge: a comprehensive survey of federated learning, TinyML and explainable AI for intrusion detection in IoT and IIoT ecosystems
AU - S. Sarath Kumar
AU - M. Asha Jerlin
PY - 2026
DA - 2026/10/19
JO - Frontiers in artificial intelligence
UR - https://europepmc.org/article/PMC/PMC13673141
SN - 2624-8212
ER -