Optimization of Network Security Intelligent Early Warning System Based on Image Matching Technology of Partial Differential Equation

Authors

  • Huan Wang Modern Education Technology Center, Hebei University of Engineering, Handan, Hebei 056038, China
  • Xin Li Academic Journal Editorial Office, Hebei University of Engineering, Handan, Hebei 056038, China

DOI:

https://doi.org/10.13052/jcsm2245-1439.1336

Keywords:

Partial differential equation, image matching, network security, intelligent early warning system

Abstract

In order to effectively avoid network information leakage and computer network paralysis, and improve the ability of computer network security early warning, it is necessary to design a computer network security intelligent early warning system based on network behavior. Security warning is considered as the second defense mechanism behind the firewall. It can monitor and warn the network without affecting the network performance, so as to provide real-time protection for external attacks, internal attacks and misoperations, and improve the network security. This paper designs an intelligent early warning system for network security based on partial differential equation image matching technology. The system adopts B/S development mode, and the server and browser are located in the campus network. Data fusion technology is used to assess network security, predict potential threats, and add new intrusion features to the feature database for subsequent use. In this paper, a target matching algorithm based on partial differential equation is proposed by using partial differential equation. The algorithm calculates the phase difference through the algebraic combination of orthogonal filter outputs. For scenes with continuous disparity changes, the error matching rate of this algorithm is lower than that of Michael Bleyer algorithm and vertical constraint algorithm. In general, the disparity map generated by this algorithm has high matching accuracy. The results show that the distribution of alarm information is reasonable and in line with the actual situation.

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Author Biographies

Huan Wang, Modern Education Technology Center, Hebei University of Engineering, Handan, Hebei 056038, China

Huan Wang was born in HanDan, China, in 1975. From 2000 to 2003, she studied in Beijing Information Science and Technology University and received her bachelor’s degree in 2003. From 2007 to 2011, she studied in Hebei University and received her master’s degree in 2011. From 2019 to 2022, she studied in Woosuk University in South Korea and received her Doctor’s degree in 2022. Currently, she works in Hebei University of Engineering. She has published ten papers, three of which have been indexed by EI. Her research interests are included the research, development, design and operation of distance education system.

Xin Li, Academic Journal Editorial Office, Hebei University of Engineering, Handan, Hebei 056038, China

Xin Li studied in Shandong Normal University and received her bachelor’s degree in 2005. From 2006 to 2008, she studied in Beijing Jiaotong University and received her master’s degree in 2008. From 2019 to 2022, she studied in University of the Cordilleras and received her Doctor’s degree in 2022. Currently, she works in Hebei University of Engineering. She has published five papers, one of which have been indexed by EI. Her research interests are digital education, education management.

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Published

2024-04-09

How to Cite

1.
Wang H, Li X. Optimization of Network Security Intelligent Early Warning System Based on Image Matching Technology of Partial Differential Equation. JCSANDM [Internet]. 2024 Apr. 9 [cited 2024 Jul. 25];13(03):461-88. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/24335

Issue

Section

Cyber Security Issues and Solutions