Abstract
The problems of building neural networks to solve the problems of detecting network intrusions, taking into account modern publicly available technologies, are considered. Several configurations of neural networks are analyzed: a simple perceptron, a combined network consisting of two interconnected networks, simplified networks based on a simple perceptron, LSTM networks using hidden layers with data compression function. The weaknesses and strengths of neural network architectures are considered, taking into account the specifics of their training based on abnormal traffic datasets in intrusion detection tasks.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of Tomsk State University of Control Systems and Radioelectronics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
