Toward design of an intelligent cyber attack detection system using hybrid feature reduced approach for iot networks
With simple connectivity and fast-growing demand of smart devices and networks, IoT has
become more prone to cyber attacks. In order to detect and prevent cyber attacks in IoT …
become more prone to cyber attacks. In order to detect and prevent cyber attacks in IoT …
Hybrid meta-heuristic based feature selection mechanism for cyber-attack detection in iot-enabled networks
Today's technologically advanced connected world is mostly reliant on the Internet of Things
(IoT)-enabled smart gadgets and easy connectivity. These smart gadgets are more …
(IoT)-enabled smart gadgets and easy connectivity. These smart gadgets are more …
[HTML][HTML] A metaheuristic-based ensemble feature selection framework for cyber threat detection in IoT-enabled networks
Abstract Internet of Things (IoT) enabled networks are highly vulnerable to cyber threats due
to insecure wireless communication, resource constraint architecture, different types of IoT …
to insecure wireless communication, resource constraint architecture, different types of IoT …
An efficient network intrusion detection model for IoT security using K-NN classifier and feature selection
M Mohy-Eddine, A Guezzaz, S Benkirane… - Multimedia Tools and …, 2023 - Springer
Abstract The Internet of Things (IoT) interconnects billions of sensors and actuators to serve
a meaningful purpose. However, it is always vulnerable to various menaces. Thus, IoT …
a meaningful purpose. However, it is always vulnerable to various menaces. Thus, IoT …
IoT intrusion detection using machine learning with a novel high performing feature selection method
The Internet of Things (IoT) ecosystem has experienced significant growth in data traffic and
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
WILS-TRS—A novel optimized deep learning based intrusion detection framework for IoT networks
B Jothi, M Pushpalatha - Personal and Ubiquitous Computing, 2023 - Springer
Abstract Internet of Things (IoT) and its applications have gained importance in recent times
of research. The heterogeneous nature of IoT networks makes them applicable for various …
of research. The heterogeneous nature of IoT networks makes them applicable for various …
[PDF][PDF] A Lightweight Hybrid Intrusion Detection Framework using Machine Learning for Edge-Based IIoT Security.
Due to the development of cloud computing and Internet of Things (IoT) environments, such
as healthcare systems, telecommunications and Industry 4.0 or Industrial IoT (IIoT) many …
as healthcare systems, telecommunications and Industry 4.0 or Industrial IoT (IIoT) many …
Attack detection in IoT using machine learning
Many researchers have examined the risks imposed by the Internet of Things (IoT) devices
on big companies and smart towns. Due to the high adoption of IoT, their character, inherent …
on big companies and smart towns. Due to the high adoption of IoT, their character, inherent …
Investigation of machine learning techniques in intrusion detection system for IoT network
SSS Sugi, SR Ratna - 2020 3rd international conference on …, 2020 - ieeexplore.ieee.org
Internet of Things (IoT) combines the internet and physical objects to transfer information
among the objects. In the emerging IoT networks, providing security is the major issue. IoT …
among the objects. In the emerging IoT networks, providing security is the major issue. IoT …
[HTML][HTML] Enhancing intrusion detection in IoT systems: A hybrid metaheuristics-deep learning approach with ensemble of recurrent neural networks
P Sanju - Journal of Engineering Research, 2023 - Elsevier
Significant benefits have been brought to various industries by IoT (Internet of Things), but
new security challenges have also been introduced due to the sheer volume and complexity …
new security challenges have also been introduced due to the sheer volume and complexity …