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Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part I

Research Article

Design of Network Traffic Anomaly Monitoring System Based on Data Mining

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-28787-9_41,
        author={Yanling Huang and Liusong Huang},
        title={Design of Network Traffic Anomaly Monitoring System Based on Data Mining},
        proceedings={Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2023},
        month={3},
        keywords={Data mining Network flow Abnormal monitoring},
        doi={10.1007/978-3-031-28787-9_41}
    }
    
  • Yanling Huang
    Liusong Huang
    Year: 2023
    Design of Network Traffic Anomaly Monitoring System Based on Data Mining
    ADHIP
    Springer
    DOI: 10.1007/978-3-031-28787-9_41
Yanling Huang1,*, Liusong Huang2
  • 1: Department of Computer and Art Design, Henan Vocational College of Light Industry
  • 2: Software Engineering, Maanshan Teacher’s College
*Contact email: kjkmgm123@163.com

Abstract

The security hidden dangers in the network will affect the normal operation of the network. Therefore, in order to better ensure the security of the network structure, it is necessary to monitor the abnormal network traffic. However, due to the low monitoring accuracy and long monitoring time of the traditional network traffic anomaly monitoring system, this paper designs a network traffic anomaly monitoring system based on data mining. Through the configuration of data acquisition equipment, analysis equipment, exception handling equipment and system management equipment, the hardware structure of the system is designed. On this basis, through the system software functions of acquisition module, data processing module, data analysis module, data application module and infrastructure management module, the abnormal monitoring of network traffic is realized through data mining. Finally, the experiment proves that the network traffic anomaly monitoring system based on data mining has higher monitoring accuracy and shorter monitoring time, which is practical in practical application and fully meets the research requirements.

Keywords
Data mining Network flow Abnormal monitoring
Published
2023-03-22
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-28787-9_41
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