[HTML][HTML] Analysis of cyber security attacks and its solutions for the smart grid using machine learning and blockchain methods
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
[HTML][HTML] A survey on feature selection techniques based on filtering methods for cyber attack detection
Y Lyu, Y Feng, K Sakurai - Information, 2023 - mdpi.com
Cyber attack detection technology plays a vital role today, since cyber attacks have been
causing great harm and loss to organizations and individuals. Feature selection is a …
causing great harm and loss to organizations and individuals. Feature selection is a …
An improved anomaly detection model for IoT security using decision tree and gradient boosting
M Douiba, S Benkirane, A Guezzaz… - The Journal of …, 2023 - Springer
Abstract Internet of Things (IoT) represents a massive deployment of connected, intelligent
devices that communicate directly in private, public, and professional environments without …
devices that communicate directly in private, public, and professional environments without …
Design and development of RNN anomaly detection model for IoT networks
I Ullah, QH Mahmoud - IEEE Access, 2022 - ieeexplore.ieee.org
Cybersecurity is important today because of the increasing growth of the Internet of Things
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …
lIDS-SIoEL: intrusion detection framework for IoT-based smart environments security using ensemble learning
Smart cities are being enabled all around the world by Internet of Things (IoT) applications.
A smart city idea necessitates the integration of information and communication …
A smart city idea necessitates the integration of information and communication …
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 …
A deep learning approach for intrusion detection in Internet of Things using focal loss function
Abstract Internet of Things (IoT) is likely to revolutionize healthcare, energy, education,
transportation, manufacturing, military, agriculture, and other industries. However, for the …
transportation, manufacturing, military, agriculture, and other industries. However, for the …
An efficient hybrid-dnn for ddos detection and classification in software-defined iiot networks
Software-defined networking (SDN)-based Industrial Internet of Things (IIoT) networks have
a centralized controller that is a single attractive target for unauthorized users to attack …
a centralized controller that is a single attractive target for unauthorized users to attack …
Cyber threats detection in smart environments using SDN-enabled DNN-LSTM hybrid framework
M Al Razib, D Javeed, MT Khan, R Alkanhel… - IEEE …, 2022 - ieeexplore.ieee.org
Internet of Things (IoT) is an instantly exacerbated communication technology that is
manifesting miraculous effectuation to revolutionize conventional means of network …
manifesting miraculous effectuation to revolutionize conventional means of network …
An optimized ensemble prediction model using AutoML based on soft voting classifier for network intrusion detection
Traditional ML based IDS cannot handle high-speed and ever-evolving attacks.
Furthermore, these traditional IDS face several common challenges, such as processing …
Furthermore, these traditional IDS face several common challenges, such as processing …