Abnormal Traffic Detection Based on Generative Adversarial Network and Feature Optimization Selection
Complex and multidimensional network traffic features have potential redundancy. When traditional detection methods are used for training samples, the detection accuracy of the supervised classification model is affected due to small data samples. Therefore, a method based on generative adversarial...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2021-03-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125954216/view |