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An Imbalanced Generative Adversarial Network-Based Approach for Network Intrusion Detection in an Imbalanced Dataset.

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第一作者： Yamarthi Narasimha,Rao

第一单位： School of Computer Science and Engineering, VIT-AP University, Amaravathi 522237, Andhra Pradesh, India.

作者： Yamarthi Narasimha,Rao ^[1] ; Kunda,Suresh Babu ^[1]

作者单位： School of Computer Science and Engineering, VIT-AP University, Amaravathi 522237, Andhra Pradesh, India. ^[1]

关键词 LSTM LeNet 5 attacks class imbalance deep learning algorithms imbalanced generative adversarial network (IGAN)intrusion detection

DOI 10.3390/s23010550

PMID 36617148

发布时间 2025-02-20

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Sensors (Basel, Switzerland)

2023年23卷1期

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An Imbalanced Generative Adversarial Network-Based Approach for Network Intrusion Detection in an Imbalanced Dataset.

Sensors (Basel, Switzerland)

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An Imbalanced Generative Adversarial Network-Based Approach for Network Intrusion Detection in an Imbalanced Dataset.

Sensors (Basel, Switzerland)

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Sensors (Basel, Switzerland)

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