A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges
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 …
Host-based IDS: A review and open issues of an anomaly detection system in IoT
Abstract The Internet of Things (IoT) envisions a smart environment powered by connectivity
and heterogeneity where ensuring reliable services and communications across multiple …
and heterogeneity where ensuring reliable services and communications across multiple …
[HTML][HTML] A machine learning-based intrusion detection for detecting internet of things network attacks
Abstract The Internet of Things (IoT) refers to the collection of all those devices that could
connect to the Internet to collect and share data. The introduction of varied devices …
connect to the Internet to collect and share data. The introduction of varied devices …
A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
Denial of service attack detection and mitigation for internet of things using looking-back-enabled machine learning techniques
Abstract IoT (Internet of Things) systems are still facing a great number of attacks due to their
integration in several areas of life. The most-reported attacks against IoT systems are" …
integration in several areas of life. The most-reported attacks against IoT systems are" …
MQTTset, a new dataset for machine learning techniques on MQTT
IoT networks are increasingly popular nowadays to monitor critical environments of different
nature, significantly increasing the amount of data exchanged. Due to the huge number of …
nature, significantly increasing the amount of data exchanged. Due to the huge number of …
Hybrid deep learning for botnet attack detection in the internet-of-things networks
Deep learning (DL) is an efficient method for botnet attack detection. However, the volume of
network traffic data and memory space required is usually large. It is, therefore, almost …
network traffic data and memory space required is usually large. It is, therefore, almost …
Protocol-based deep intrusion detection for dos and ddos attacks using unsw-nb15 and bot-iot data-sets
Since its inception, the Internet of Things (IoT) has witnessed mushroom growth as a
breakthrough technology. In a nutshell, IoT is the integration of devices and data such that …
breakthrough technology. In a nutshell, IoT is the integration of devices and data such that …
Unified deep learning approach for efficient intrusion detection system using integrated spatial–temporal features
PR Kanna, P Santhi - Knowledge-Based Systems, 2021 - Elsevier
Intrusion detection systems (IDS) differentiate the malicious entries from the legitimate
entries in network traffic data and helps in securing the networks. Deep learning algorithms …
entries in network traffic data and helps in securing the networks. Deep learning algorithms …
XGBoost for imbalanced multiclass classification-based industrial internet of things intrusion detection systems
The Industrial Internet of Things (IIoT) has advanced digital technology and the fastest
interconnection, which creates opportunities to substantially grow industrial businesses …
interconnection, which creates opportunities to substantially grow industrial businesses …