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Iterative per Group Feature Selection for Intrusion Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Network security is an critical subject in any distributed network. Recently, machine learning has proven their efficiency for intrusion detection. By using a comprehensive dataset with multiple attack types, a well-trained ...
Weighted Trustworthiness for ML Based Attacks Classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Recently, machine learning techniques are gaining a lot of interest in security applications as they exhibit fast processing with real-time predictions. One of the significant challenges in the implementation of these ...
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 ...