This paper presents a neural network model which was developed and trained to detect attacks on computer networks and to identify the differences indicating what distinguishes them from the regular network traffic. The influence of some parameters on the operation of the network was examined in order to select those characteristic for cyberattack. A certain number of models was tested for binary and multi-class classification. The accuracy of recognition by the network was evaluated for both the entire set and individual categories of the network traffic. The results obtained are promising based on comparison to those published in related work studies on intrusion detection systems.
Paper
Full text
Detecting Attacks on Computer Networks Using Artificial Intelligence Algorithms
Semantic Scholar · Computer Science · 2022
Abstract
This paper presents a neural network model which was developed and trained to detect attacks on computer networks and to identify the differences indicating what distinguishes them from the regular network traffic. The influence of some parameters on the operation of the network was examined in order to select those characteristic for cyberattack. A certain number of models was tested for binary and multi-class classification. The accuracy of recognition by the network was evaluated for both the entire set and individual categories of the network traffic. The results obtained are promising based on comparison to those published in related work studies on intrusion detection systems.