Jul 20, 2021 · This paper proposes a hierarchical packet byte-based CNN, called PBCNN, where the first level extracts abstract features automatically from bytes in a packet ...
Network intrusion detection system (IDS) protects the target network from the threats of data breaches and insecurity of people's privacy.
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This paper innovatively organizes the studied CNN-IDS approaches into multiple categories and describes their primary capabilities and contributions.
This paper proposes a hierarchical packet byte-based CNN model to improve the reliability of network intrusion detection through feature extraction and few ...
Yu et al., “PBCNN: Packet Bytes-based. Convolutional Neural Network for Network Intrusion. Detection,” Comput. Networks, vol. 194, no. March, p. 108117, 2021 ...
PBCNN: Packet Bytes-based Convolutional Neural Network for Network Intrusion Detection. Comput. Netw. 2021, 194, 108117. [Google Scholar] [CrossRef]; Crowley ...
Apr 20, 2023 · This paper utilizes few-shot learning to solve the data imbalance problem caused by insufficient samples in network intrusion detection.
This work proposes three models, two deep learning convolutional neural networks (CNN), long short-term memory (LSTM), and Apache Spark, to improve the ...
This paper innovatively organizes the studied CNN-IDS approaches into multiple categories and describes their primary capabilities and contributions.
Jan 12, 2022 · Yu et al. (23) had proposed a packet byte-based CNN, called PBCNN, which focuses on the statistical features of network traffic, giving another ...
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