Cargando…
A lightweight intrusion detection method for IoT based on deep learning and dynamic quantization
Intrusion detection ensures that IoT can protect itself against malicious intrusions in extensive and intricate network traffic data. In recent years, deep learning has been extensively and effectively employed in IoT intrusion detection. However, the limited computing power and storage space of IoT...
Autores principales: | Wang, Zhendong, Chen, Hui, Yang, Shuxin, Luo, Xiao, Li, Dahai, Wang, Junling |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557502/ https://www.ncbi.nlm.nih.gov/pubmed/37810346 http://dx.doi.org/10.7717/peerj-cs.1569 |
Ejemplares similares
-
Machine learning and deep learning approaches in IoT
por: Javed, Abqa, et al.
Publicado: (2023) -
IoT-based intrusion detection system using convolution neural networks
por: Aljumah, Abdullah
Publicado: (2021) -
IoT based smart home automation using blockchain and deep learning models
por: Umer, Muhammad, et al.
Publicado: (2023) -
SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
por: Mohammadi, Ramin, et al.
Publicado: (2023) -
Impact of green technology innovation based on IoT and industrial supply chain on the promotion of enterprise digital economy
por: Song, Ruilin, et al.
Publicado: (2023)