Intrusion Detection Method Based on Wasserstein Generative Adversarial Network

Qing Zou; Wenbo Guan

doi:10.1109/icfeict57213.2022.00109

ScienceGate Book Chapters

JOURNAL ARTICLE

Intrusion Detection Method Based on Wasserstein Generative Adversarial Network

Qing Zou Wenbo Guan

Year: 2022 Journal: 2022 2nd International Conference on Frontiers of Electronics, Information and Computation Technologies (ICFEICT) Pages: 599-603

DOI: 10.1109/icfeict57213.2022.00109

Get Full-Text PDF Get Analytical Report

Keywords:

Adversarial system Computer science Generative adversarial network Intrusion detection system Generative grammar Artificial intelligence Pattern recognition (psychology) Deep learning

Metrics

Cited By

0.28

FWCI (Field Weighted Citation Impact)

Refs

0.60

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Digital Media Forensic Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Generative Adversarial Networks and Image Synthesis

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Intrusion Detection Method Based on Wasserstein Generative Adversarial Network

Metrics

Citation History

Topics

Related Documents

One-Dimensional Convolutional Wasserstein Generative Adversarial Network Based Intrusion Detection Method for Industrial Control Systems

Intrusion Detection Method Based on Autoencoder Generative Adversarial Network

Network Intrusion Detection Based on Conditional Wasserstein Generative Adversarial Network and Cost-Sensitive Stacked Autoencoder

Research on Intrusion Detection Method Based on Generative Adversarial Network

Intrusion Detection Method Based On Improved Conditional Generative Adversarial Network