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Regression is one of the techniques of machine learning. Most of the contributions in the literature in respect to intrusion detection are mainly based on dimensionality reduction using techniques such as PCA, SVD, feature selection, feature reduction techniques and application of classifier algorithms.
Jun 4, 2021 · Regression analysis may be applied for dimensionality reduction, classification or prediction tasks. This paper throws light on the possibility ...
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This study proposes an efficient approach based on a logistic regression model trained by a parallel artificial bee colony algorithm for network intrusion ...
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May 24, 2024 · This research investigates the application of machine learning models for network intrusion detection in the context of Social Internet of ...
Mar 24, 2021 · For detecting malicious activities in the network, we developed correlation and regression based network intrusion detection for Internet of ...
While these methods can accomplish excellent functionality, their accuracy is comparatively low and rely heavily on manual identification of network threats.
To overcome the deficiencies of low accuracy and high false alarm rate in network intrusion detection system, an integrated Intrusion detection model based ...
Jan 4, 2022 · Due to the effectiveness of machine learning (ML) methods, the proposed approach applied several ML models for the intrusion detection system.
Sep 6, 2024 · BAT is a network anomaly detection model that has been developed combining Liner Regression, 3 Layer Neural Network and attention mechanism.
This paper proposes and evaluates computer network security using data fusion and data mining methods to combine (Distributed Intrusion Detection System)DIDS.