Internet of things (IoT) security dataset evolution: Challenges and future directions
The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
Deep learning for intrusion detection and security of Internet of things (IoT): current analysis, challenges, and possible solutions
In the last decade, huge growth is recorded globally in computer networks and Internet of
Things (IoT) networks due to the exponential data generation, approximately zettabyte to a …
Things (IoT) networks due to the exponential data generation, approximately zettabyte to a …
The role of machine learning in network anomaly detection for cybersecurity
A Yaseen - Sage Science Review of Applied Machine …, 2023 - journals.sagescience.org
This research introduces a theoretical framework for network anomaly detection in
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …
[HTML][HTML] A new two-phase intrusion detection system with Naïve Bayes machine learning for data classification and elliptic envelop method for anomaly detection
M Vishwakarma, N Kesswani - Decision Analytics Journal, 2023 - Elsevier
Technology is pivotal in the rapid growth of services and intensifying the quality of life.
Recent technology, like the Internet of Things (IoT), demonstrates an impressive …
Recent technology, like the Internet of Things (IoT), demonstrates an impressive …
[HTML][HTML] Enhancing IoT network security through deep learning-powered Intrusion Detection System
The rapid growth of the Internet of Things (IoT) has brought about a global concern for the
security of interconnected devices and networks. This necessitates the use of efficient …
security of interconnected devices and networks. This necessitates the use of efficient …
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 …
An ensemble learning based intrusion detection model for industrial IoT security
M Mohy-Eddine, A Guezzaz… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) represents the expansion of the Internet of Things (IoT) in
industrial sectors. It is designed to implicate embedded technologies in manufacturing fields …
industrial sectors. It is designed to implicate embedded technologies in manufacturing fields …
Cyber threats detection in smart environments using SDN-enabled DNN-LSTM hybrid framework
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 …
Anomaly-based intrusion detection system for IoT application
Abstract Internet-of-Things (IoT) connects various physical objects through the Internet and it
has a wide application, such as in transportation, military, healthcare, agriculture, and many …
has a wide application, such as in transportation, military, healthcare, agriculture, and many …
Fog-cloud based intrusion detection system using Recurrent Neural Networks and feature selection for IoT networks
Deep learning (DL) techniques are being widely researched for their effectiveness in
detecting cyber intrusions against the Internet of Things (IoT). Time sensitive Critical …
detecting cyber intrusions against the Internet of Things (IoT). Time sensitive Critical …