Building Auto-Encoder Intrusion Detection System based on random forest feature selection

Machine learning techniques have been widely used in intrusion detection for many years. However, these techniques are still suffer from lack of labeled dataset, heavy overhead and low accuracy. To improve classification accuracy and reduce training time, this paper proposes an effective deep learni...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Computers & security Ročník 95; s. 101851 - 15
Hlavní autoři:	Li, XuKui, Chen, Wei, Zhang, Qianru, Wu, Lifa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier Ltd 01.08.2020 Elsevier Sequoia S.A
Témata:	Accuracy Algorithms Auto-Encoder Classification Coders Deep learning Feature selection Intrusion Intrusion detection systems Machine learning Network Intrusion Detection System Network security Training Unsupervised clustering Deep learning Network security Network Intrusion Detection System Auto-Encoder Unsupervised clustering
ISSN:	0167-4048, 1872-6208
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!