Cargando…
Advanced Feature Extraction and Selection Approach Using Deep Learning and Aquila Optimizer for IoT Intrusion Detection System
Developing cyber security is very necessary and has attracted considerable attention from academy and industry organizations worldwide. It is also very necessary to provide sustainable computing for the the Internet of Things (IoT). Machine learning techniques play a vital role in the cybersecurity...
Autores principales: | Fatani, Abdulaziz, Dahou, Abdelghani, Al-qaness, Mohammed A. A., Lu, Songfeng, Elaziz, Mohamed Abd |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749550/ https://www.ncbi.nlm.nih.gov/pubmed/35009682 http://dx.doi.org/10.3390/s22010140 |
Ejemplares similares
-
Enhancing Intrusion Detection Systems for IoT and Cloud Environments Using a Growth Optimizer Algorithm and Conventional Neural Networks
por: Fatani, Abdulaziz, et al.
Publicado: (2023) -
Intrusion Detection System for IoT Based on Deep Learning and Modified Reptile Search Algorithm
por: Dahou, Abdelghani, et al.
Publicado: (2022) -
Boosting COVID-19 Image Classification Using MobileNetV3 and Aquila Optimizer Algorithm
por: Abd Elaziz, Mohamed, et al.
Publicado: (2021) -
Medical Image Classifications for 6G IoT-Enabled Smart Health Systems
por: Elaziz, Mohamed Abd, et al.
Publicado: (2023) -
A Novel Hybrid Gradient-Based Optimizer and Grey Wolf Optimizer Feature Selection Method for Human Activity Recognition Using Smartphone Sensors
por: Helmi, Ahmed Mohamed, et al.
Publicado: (2021)