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Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
Machine Learning Based Cloud Computing Anomalies Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
A Weighted Machine Learning-Based Attacks Classification to Alleviating Class Imbalance
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The Industrial Internet of Things (IIoT) has become very popular in recent years. However, IIoT is still an attractive and vulnerable target for attackers to exploit and experiment with different types of attacks. To ...
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Machine learning techniques are becoming mainstream in intrusion detection systems as they allow real-time response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a ...
Efficient techniques for energy saving in data center networks
(
Elsevier B.V.
, 2018 , Article)
Data centers are constructed with a huge number of network devices to support the expanding cloud based services. These devices are used to achieve the highest performance in case of full utilization of the network. However, ...