Detecting Attacks Using Artificial Neural Networks

The developed neural network attack detection algorithm, whose peculiarity lies in the possibility of launching two parallel processes, is described: searching for the optimal model of an artificial neural network and normalization of the training sample data. It is shown that the artificial neural...

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Veröffentlicht in:	Automatic control and computer sciences Jg. 58; H. 8; S. 1218 - 1225
Hauptverfasser:	Sikarev, I. A., Tatarnikova, T. M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Moscow Pleiades Publishing 01.12.2024 Springer Nature B.V
Schlagworte:	Algorithms Artificial neural networks Computer Science Control Structures and Microprogramming Datasets Neural networks Software Special libraries artificial neural network loss function intrusion detection system training classification dataset architecture optimization
ISSN:	0146-4116, 1558-108X
Online-Zugang:	Volltext
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