Huge data over the cloud computing and big data are processed over the network. The data may be stored, send, altered and communicated over the network ...
This hybrid machine learning algorithm in feature extraction process helps to find attacked information using recursive function.
In this paper, we present a real-time face detection method based on hybrid neural networks. We propose a modified version of fuzzy min-max (FMM) neural network ...
Abstract: Huge data over the cloud computing and big data are processed over the network. The data may be stored, send, altered and communicated over the ...
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In this research, we propose a Feed-Forward Deep Neural Network (FFDNN) wireless IDS system using a Wrapper Based Feature Extraction Unit (WFEU).
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Feb 5, 2023 · This paper proposes IGRF-RFE: a hybrid feature selection method tasked for multi-class network anomalies using a multilayer perceptron (MLP) network.
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Apr 14, 2023 · A convolutional recurrent neural network is employed in this study to construct a deep-learning-based hybrid intrusion detection system that detects attacks ...
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The comparative analysis of network intrusion detection methods focuses on accuracy and false positive rate. GBA shines with exceptional results: achieving ...
Sep 4, 2023 · Four hybrid intrusion detection systems for satellite-terrestrial communication systems (SAT-IDSs) are proposed in this paper.
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May 23, 2024 · A hybrid feature weighted attention based deep learning approach for an intrusion detection system using the random forest algorithm