WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches

Research article (Computers, 2024) · cited 12× · AI/ML
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches

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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches. Retrieved May 24, 2026, from https://4ort.xyz/entity/wgan-dl-ids-an-efficient-framework-for-intrusion-detection-system-using-wgan-random-forest-and-deep-learning-approaches
MLA “WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/wgan-dl-ids-an-efficient-framework-for-intrusion-detection-system-using-wgan-random-forest-and-deep-learning-approaches.
BibTeX @misc{4ortxyz_wgan-dl-ids-an-efficient-framework-for-intrusion-detection-system-using-wgan-random-forest-and-deep-learning-approaches_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches}}, year = {2026}, url = {https://4ort.xyz/entity/wgan-dl-ids-an-efficient-framework-for-intrusion-detection-system-using-wgan-random-forest-and-deep-learning-approaches}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches — https://4ort.xyz/entity/wgan-dl-ids-an-efficient-framework-for-intrusion-detection-system-using-wgan-random-forest-and-deep-learning-approaches (retrieved 2026-05-24)

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