Title: Simulation and application of computer network security monitoring based on multi-difference embedded model

Authors: Yuping Li; Ke Li

Addresses: School of Information Technology, Shangqiu Normal University, Shangqiu 476000, Henan, China ' School of Information Technology, Shangqiu Normal University, Shangqiu 476000, Henan, China

Abstract: In order to strengthen the maintenance of computer network security, this article uses the multi-differential embedding model to monitor, simulate and apply research on computer network security. This article analyses the accuracy, stability and time period of network security through application experiments on two computers of different brands (Dell Precision 3551 and HP ZBook Fury 17 G7). The results showed that the neural network algorithm model had the highest average accuracy, with Dell Precision 3551 at 93.3% and HP ZBook Fury 17 G7 at 95.6%. The Math OS model had the highest average stability, with the Dell Precision 3551 at 77.5% and the HP ZBook Fury 17 G7 at 77.7%. The mathematical operating system model on the Dell Precision 3551 had the shortest average time period at 32.8 seconds, and the UML model on the HP ZBook Fury 17 G7 had the shortest time period at 30.6 seconds.

Keywords: computer network security; neural network algorithm; embedded model; unified modelling language; UML; network security monitoring.

DOI: 10.1504/IJES.2023.141934

International Journal of Embedded Systems, 2023 Vol.16 No.5/6, pp.364 - 374

Received: 11 Apr 2023
Accepted: 25 Aug 2023
Published online: 03 Oct 2024 *

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