[HTML][HTML] IoT intrusion detection taxonomy, reference architecture, and analyses
This paper surveys the deep learning (DL) approaches for intrusion-detection systems
(IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps …
(IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps …
[HTML][HTML] Anomaly-based intrusion detection systems in iot using deep learning: A systematic literature review
The Internet of Things (IoT) concept has emerged to improve people's lives by providing a
wide range of smart and connected devices and applications in several domains, such as …
wide range of smart and connected devices and applications in several domains, such as …
On the performance of machine learning models for anomaly-based intelligent intrusion detection systems for the internet of things
G Abdelmoumin, DB Rawat… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Anomaly-based machine learning-enabled intrusion detection systems (AML-IDSs) show
low performance and prediction accuracy while detecting intrusions in the Internet of Things …
low performance and prediction accuracy while detecting intrusions in the Internet of Things …
Deep learning in IoT intrusion detection
Abstract The Internet of Things (IoT) is the new paradigm of our times, where smart devices
and sensors from across the globe are interconnected in a global grid, and distributed …
and sensors from across the globe are interconnected in a global grid, and distributed …
[HTML][HTML] A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and …
A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
[HTML][HTML] Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning
Abstract Internet of Things (IoT) devices are widely used but also vulnerable to cyberattacks
that can cause security issues. To protect against this, machine learning approaches have …
that can cause security issues. To protect against this, machine learning approaches have …
Internet of Things intrusion detection systems: a comprehensive review and future directions
A Heidari, MA Jabraeil Jamali - Cluster Computing, 2023 - Springer
Abstract The Internet of Things (IoT) is a paradigm that connects objects to the Internet as a
whole and enables them to work together to achieve common objectives, such as innovative …
whole and enables them to work together to achieve common objectives, such as innovative …
A Survey of Deep Learning Technologies for Intrusion Detection in Internet of Things
The Internet of Things (IoT) is transforming how we live and work, and its applications are
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
Intrusion Detection Systems for IoT: opportunities and challenges offered by Edge Computing and Machine Learning
P Spadaccino, F Cuomo - arXiv preprint arXiv:2012.01174, 2020 - arxiv.org
Key components of current cybersecurity methods are the Intrusion Detection Systems
(IDSs) were different techniques and architectures are applied to detect intrusions. IDSs can …
(IDSs) were different techniques and architectures are applied to detect intrusions. IDSs can …
[HTML][HTML] 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 …