Network intrusion detection based on conditional wasserstein variational autoencoder with generative adversarial network and one-dimensional convolutional neural networks
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1573-7497
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Network intrusion detection based on conditional wasserstein variational autoencoder with generative adversarial network and one-dimensional convolutional neural networks ; day:27 ; month:9 ; year:2022 ; pages:1-21
Applied intelligence ; (27.9.2022), 1-21
- Urheber
-
He, Jiaxing
Wang, Xiaodan
Song, Yafei
Xiang, Qian
Chen, Chen
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s10489-022-03995-2
- URN
-
urn:nbn:de:101:1-2022121521000533266924
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:26 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- He, Jiaxing
- Wang, Xiaodan
- Song, Yafei
- Xiang, Qian
- Chen, Chen
- SpringerLink (Online service)
Ähnliche Objekte (12)
Improved Wasserstein conditional generative adversarial network speech enhancement
Network Intrusion Detection System Based on an Adversarial Auto-Encoder with Few Labeled Training Samples
Network intrusion detection
Sliced Wasserstein adversarial training for improving adversarial robustness
A network intrusion detection framework on sparse deep denoising auto-encoder for dimensionality reduction
Oblivious network intrusion detection systems
Simulating multi-asset classes prices using Wasserstein Generative Adversarial Network: A study of stocks, futures and cryptocurrency
Facial landmark disentangled network with variational autoencoder
Enhanced network optimized generative adversarial network for image enhancement
Semantic Models for Network Intrusion Detection
Optimization of network intrusion detection processes
Adversarial classification via distributional robustness with Wasserstein ambiguity
Improved Wasserstein conditional generative adversarial network speech enhancement
Network Intrusion Detection System Based on an Adversarial Auto-Encoder with Few Labeled Training Samples
Network intrusion detection
Sliced Wasserstein adversarial training for improving adversarial robustness
A network intrusion detection framework on sparse deep denoising auto-encoder for dimensionality reduction
Oblivious network intrusion detection systems
Simulating multi-asset classes prices using Wasserstein Generative Adversarial Network: A study of stocks, futures and cryptocurrency
Facial landmark disentangled network with variational autoencoder
Enhanced network optimized generative adversarial network for image enhancement
Semantic Models for Network Intrusion Detection
Optimization of network intrusion detection processes
Adversarial classification via distributional robustness with Wasserstein ambiguity
Improved Wasserstein conditional generative adversarial network speech enhancement
Network Intrusion Detection System Based on an Adversarial Auto-Encoder with Few Labeled Training Samples
Network intrusion detection
Sliced Wasserstein adversarial training for improving adversarial robustness
A network intrusion detection framework on sparse deep denoising auto-encoder for dimensionality reduction
Oblivious network intrusion detection systems
Simulating multi-asset classes prices using Wasserstein Generative Adversarial Network: A study of stocks, futures and cryptocurrency
Facial landmark disentangled network with variational autoencoder
Enhanced network optimized generative adversarial network for image enhancement
Semantic Models for Network Intrusion Detection
Optimization of network intrusion detection processes