Cargando…
An Effective Feature Selection Model Using Hybrid Metaheuristic Algorithms for IoT Intrusion Detection
The increasing use of Internet of Things (IoT) applications in various aspects of our lives has created a huge amount of data. IoT applications often require the presence of many technologies such as cloud computing and fog computing, which have led to serious challenges to security. As a result of...
Autores principales: | Kareem, Saif S., Mostafa, Reham R., Hashim, Fatma A., El-Bakry, Hazem M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962996/ https://www.ncbi.nlm.nih.gov/pubmed/35214297 http://dx.doi.org/10.3390/s22041396 |
Ejemplares similares
-
A Novel Feature-Selection Algorithm in IoT Networks for Intrusion Detection
por: Nazir, Anjum, et al.
Publicado: (2023) -
The proposed hybrid deep learning intrusion prediction IoT (HDLIP-IoT) framework
por: Fadel, Magdy M., et al.
Publicado: (2022) -
Attentive transformer deep learning algorithm for intrusion detection on IoT systems using automatic Xplainable feature selection
por: Zegarra Rodríguez, Demóstenes, et al.
Publicado: (2023) -
Towards an Explainable Universal Feature Set for IoT Intrusion Detection
por: Alani, Mohammed M., et al.
Publicado: (2022) -
ST-AL: a hybridized search based metaheuristic computational algorithm towards optimization of high dimensional industrial datasets
por: Mostafa, Reham R., et al.
Publicado: (2022)