Research review for broad learning system: Algorithms, theory, and applications
In recent years, the appearance of the broad learning system (BLS) is poised to
revolutionize conventional artificial intelligence methods. It represents a step toward building …
revolutionize conventional artificial intelligence methods. It represents a step toward building …
[PDF][PDF] Towards Machine Learning Based Intrusion Detection in IoT Networks.
The Internet of Things (IoT) integrates billions of self-organized and heterogeneous smart
nodes that communicate with each other without human intervention. In recent years, IoT …
nodes that communicate with each other without human intervention. In recent years, IoT …
Stacked one-class broad learning system for intrusion detection in industry 4.0
With the vigorous development of Industry 4.0, industrial Big Data has turned into the core
element of the Industrial Internet of Things. As one of the most fundamental and …
element of the Industrial Internet of Things. As one of the most fundamental and …
Machine learning techniques for classifying network anomalies and intrusions
Using machine learning techniques to detect network intrusions is an important topic in
cybersecurity. A variety of machine learning models have been designed to help detect …
cybersecurity. A variety of machine learning models have been designed to help detect …
Machine learning for detecting anomalies and intrusions in communication networks
Cyber attacks are becoming more sophisticated and, hence, more difficult to detect. Using
efficient and effective machine learning techniques to detect network anomalies and …
efficient and effective machine learning techniques to detect network anomalies and …
Analysis of anomaly detection approaches performed through deep learning methods in SCADA systems
Supervisory control and data acquisition (SCADA) systems are used with monitoring and
control purposes for the process not to fail in industrial control systems. Today, the increase …
control purposes for the process not to fail in industrial control systems. Today, the increase …
Detection of denial of service attacks in communication networks
Detection of evolving cyber attacks is a challenging task for conventional network intrusion
detection techniques. Various supervised machine learning algorithms have been …
detection techniques. Various supervised machine learning algorithms have been …
An efficient network intrusion detection approach based on deep learning
Z Wang, D Jiang, L Huo, W Yang - Wireless Networks, 2021 - Springer
With the rapid development of cloud computing and mobile internet, massive network traffic
is generated, with the raging malicious traffic and attacks. Network Intrusion Detection …
is generated, with the raging malicious traffic and attacks. Network Intrusion Detection …
Broad learning extreme learning machine for forecasting and eliminating tremors in teleoperation
Q Yang, K Liang, T Su, K Geng, M Pan - Applied Soft Computing, 2021 - Elsevier
Unwanted errors caused by hand tremors are a bottleneck for the application of
teleoperation robots in space explorations, underwater explorations, and minimally invasive …
teleoperation robots in space explorations, underwater explorations, and minimally invasive …
Network intrusion detection via tri-broad learning system based on spatial-temporal granularity
Network intrusion detection system plays a crucial role in protecting the integrity and
availability of sensitive assets, where the detected traffic data contain a large amount of time …
availability of sensitive assets, where the detected traffic data contain a large amount of time …