Home ›
Entities
› academia
› Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks
Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks
Research article (Discover Internet of Things, 2025) · cited 16× · AI/ML
Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks
Summary
Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks is a scholarly article[1].
Key Facts
Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/federated-learning-based-hybrid-convolutional-recurrent-neural-network-for-multi-class-intrusion-detection-in-iot-networ