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A novel method for intrusion detection in computer networks by identifying multivariate outliers and ReliefF feature selection
(SPRINGER LONDON LTD, 2022)
The identification of unusual data in computer networks is a critical task for intrusion detection systems. In this study, a novel approach has been proposed for improving intrusion detection system performance by finding ...
An Effective Classifier Model for Imbalanced Network Attack Data
(Tech Science Press, 2022)
Recently, machine learning algorithms have been used in the detection and classification of network attacks. The performance of the algorithms has been evaluated by using benchmark network intrusion datasets such as DARPA98, ...
Real-time stress detection from smartphone sensor data using genetic algorithm-based feature subset optimization and k-nearest neighbor algorithm
(SPRINGER, 2023)
Stress is the mood of pressure and tension that a person feels. Usually, when the pressure on an individual decrease, the body begins to stabilize the state and calm down. Hence, stress detection in real-time is a critical ...