An insight of deep learning based demand forecasting in smart grids
JM Aguiar-Pérez, MÁ Pérez-Juárez - Sensors, 2023 - mdpi.com
Smart grids are able to forecast customers' consumption patterns, ie, their energy demand,
and consequently electricity can be transmitted after taking into account the expected …
and consequently electricity can be transmitted after taking into account the expected …
Network intrusion detection using oversampling technique and machine learning algorithms
The expeditious growth of the World Wide Web and the rampant flow of network traffic have
resulted in a continuous increase of network security threats. Cyber attackers seek to exploit …
resulted in a continuous increase of network security threats. Cyber attackers seek to exploit …
Mitigating cyber threats through integration of feature selection and stacking ensemble learning: the LGBM and random forest intrusion detection perspective
AK Mishra, S Paliwal - Cluster Computing, 2023 - Springer
The network traffic has observed astounding expansion and is set to explode in the next few
years. Security attacks are becoming more and more synchronized as attackers are involved …
years. Security attacks are becoming more and more synchronized as attackers are involved …
A deep learning-based multi-agent system for intrusion detection
Intrusion detection systems play an important role in preventing attacks which have been
increased rapidly due to the dependence on network and Internet connectivity. Deep …
increased rapidly due to the dependence on network and Internet connectivity. Deep …
[HTML][HTML] Machine Learning in Information and Communications Technology: A Survey
The rapid growth of data and the increasing complexity of modern networks have driven the
demand for intelligent solutions in the information and communications technology (ICT) …
demand for intelligent solutions in the information and communications technology (ICT) …
[PDF][PDF] IoT network attack detection using supervised machine learning
The use of supervised learning algorithms to detect malicious traffic can be valuable in
designing intrusion detection systems and ascertaining security risks. The Internet of things …
designing intrusion detection systems and ascertaining security risks. The Internet of things …
Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context
Industry 4.0 requires high levels of autonomy in order to guarantee the manufacturing
processes to achieve production goals. For this, it is needed high levels of coordination …
processes to achieve production goals. For this, it is needed high levels of coordination …
Understanding machine learning concepts
JM Aguiar-Pérez, MA Pérez-Juárez… - Encyclopedia of Data …, 2023 - igi-global.com
Artificial intelligence can be seen as the intelligence exhibited by machines. For an artificial
intelligence system to be able to take decisions based on the data available, different type of …
intelligence system to be able to take decisions based on the data available, different type of …
Mitigating DoS attacks in IoT using supervised and unsupervised algorithms–a survey
IoT is an evolving technology used in enormous applications in order to reduce the human
intervention. As IoT is used in hybrid environment where it has to enable communication …
intervention. As IoT is used in hybrid environment where it has to enable communication …
[PDF][PDF] AID4I: An Intrusion Detection Framework for Industrial Internet of Things Using Automated Machine Learning.
By identifying and responding to any malicious behavior that could endanger the system, the
Intrusion Detection System (IDS) is crucial for preserving the security of the Industrial Internet …
Intrusion Detection System (IDS) is crucial for preserving the security of the Industrial Internet …