基于Adam-BNDNN的网络入侵检测模型.

Aiming at the problems of low detection accuracy and high false alarm rate of traditional intrusion detection algorithm, a network intrusion detection model combining batch normalization and deep neural network is proposed. Firstly, a batch normalization layer is added to the hidden layer of the dee...

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Detalles Bibliográficos

Publicado en:	Studia Poliana no. 22; pp. 58 - 64
Autores principales:	何梦乙, 覃仁超, 刘建兰, 熊健, 唐风扬
Formato:	Artículo
Publicado:	Studia Poliana 2020
Materias:	False alarms Mathematical optimization Neural circuitry Algorithms Feasibility studies
Acceso en línea:	Ver este registro en EBSCOhost